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The basic purpose of this study is to increase the installation rate of mobile games and their life cycle. Little research has been conducted into the competitive market of mobile games and word-of-mouth (WOM), advertisement and quality simultaneously. In this paper, the authors aim to assist developers with a better understanding of how to invest in the game industry.

The primitive modeling has been made based on the Bass diffusion model and its extensions using features related to the game industry. Modeling and simulation have been performed using the system dynamics method.

The results show that if game developers only focus on advertising at the introduction of the game to the market, and neglect quality features, uninstall rate of adopters increases and the game life cycle decreases. And if developers only focus on the quality improvement of the game, and ignore advertisement, they couldn't create enough WOM and thus game installation wouldn't grow enough to create revenue. Furthermore, as long as the pleasure of the game is high for its adopters, developers shouldn't give up on investing in advertising to create even higher WOM. And also in communities with higher levels of variety-seeking among game players, quality is important at the start and advertisement is vital in the following steps of the game life cycle. And if the contact rate among people is high, developers could focus on quality more than the advertisement.

Even though WOM in mobile game installation is crucial, fewer studies have been done in this area and they only address the problem using qualitative or statistical methods. The quantitative system dynamics approach based on the Bass diffusion model, used in this research, fixes the shortcomings of the previous studies. Moreover, due to serious competition in the mobile game industry, only those developers can remain in the market who can predict the future trend of the game market. Furthermore, game development is a creative process and its key factors include engaging the gamers and monetizing.

The aim of this study is to examine the trend over time of the demand for .it domain names.This study first assesses whether there is a phase of growth and expansion or at a point of saturation. Second, this research can be useful also to compare researches that have considered other internet metrics and other models.

This paper describes the forecasting methods used to analyze the internet diffusion in Italy. The domain names under the country code top-level domain “.it” have used as metrics. To predict domain names .it the seasonal auto regressive integrated moving average (SARIMA) model and the Holt-Winters (H-W) methods have been used.

The results show that, to predict domain names .it the SARIMA model is better than the H-W methods. According to the findings, notwithstanding the forecast of a growth in domain names, the increase is however limited (about 3%), tending to reach a phase of saturation of the market of domain names .it.

In general many authors have studied internet diffusion applying statistical models that follow an S-shaped behavior. On the other hand, the more used diffusion models that follow an S-shape not always provide an adequate description of the Internet growth pattern. To achieve this goal, this paper demonstrates how the time series models, in particular SARIMA model and H-W models, fit well in explaining the spread of the internet.

This paper aimed to test a proposed framework highlighting strategic green marketing initiatives and how they drive new technology implementation towards green corporate performance, underpinned by institutional isomorphism.

The study used a quantitative method and convenience sampling approach in gathering data using adapted questionnaires to solicit first-hand information from 225 employees of small and medium-sized enterprises (SMEs) in the tourism and hospitality sector underpinned by the theory of institutional isomorphism.

The study shows that green communication and green strategy alignment have significant predictive effects on new technology implementation. Cultural isomorphism significantly moderated the effects of implementing new technology (i.e. green communication and strategy alignment). In addition, “new technology implementation had a significant predictive effect on green corporate performance”. Meanwhile, the moderation effect of “green creative behaviour on the new technology-green corporate performance dyad was positive but insignificant.”

The study’s novel framework confirms how green communication strategy and green strategy alignment complement cultural isomorphism to explain the impact of new technology implementation on green corporate performance, underpinned by institutional isomorphism.

This study aims to investigate the factors influencing the adoption intention of artificial intelligence (AI) by micro, small and medium enterprises (MSMEs) in Jordan.

The study adopts the technology–organization–environment (TOE) model. It examines the moderating effects of innovation culture, employee digital skill level and market competition on the relationships between the independent and dependent variables. A survey was utilized to collect data from 537 MSME owners or managers in Jordan and employed partial least squares structural equation modeling to test the hypotheses.

The results of the study support seven out of eight hypotheses. Business innovativeness, management support, perceived benefits and technological infrastructure have positive and significant effects on AI adoption intention, while perceived costs have no significant effect. However, the innovation culture, employee digital skill level and market competition were found to moderate the relationships between some of the independent variables and dependent variables.

The study provides valuable insights and recommendations for MSME owners, managers, employees, policymakers, educators and researchers interested in promoting and facilitating AI adoption by MSMEs in Jordan.

The current attempt extends the TOE framework by adding significant constructs representing the three contexts. Moreover, it is one of the few studies that analyzed the factors influencing the adoption intention of AI by MSMEs in Jordan, which are significant to the Jordanian economy and represent 99.5% of enterprises.

This study aims to explore and conceptualize metaverse adoption using a systematic literature review (SLR). It also aims to propose a conceptual model that identifies significant factors affecting metaverse adoption in the entertainment, education, tourism and health sectors.

A SLR was conducted using the “preferred reporting items for systematic reviews and meta-analyses” report protocol and the “theory, context, characteristics, methods” framework to include all relevant articles published up to March 2023, which were sourced from the Scopus and Web of Science databases.

The reviewed literature revealed that the countries with the highest publications in the field of metaverse were China and the USA. It was also found that the technology acceptance model was the most used theoretical framework. Survey-based research using purposive and convenience sampling techniques emerged as the predominant method for data collection, and partial least square-structural equation modeling was the most used analytical technique. The review also identified the top six journals and the variables that help to develop a proposed model.

This review presents a novel contribution to the literature on metaverse adoption by forming a conceptual model that incorporates the most used variables in the entertainment, education, tourism and health sectors. The possible directions for future research with identified research gaps were also discussed.

This paper aimed to identify the impact that Industry 4.0 can have on the service sector and how its combination can generate benefits for Sustainability 4.0 in the context of the Triple Bottom Line.

A Systematic Literature Review (RSL) was developed using the following combinations of keywords on the Web of Science and Scopus databases: Industry 4.0 And Sustainability, Industry 4.0 And Service, and Industry 4.0 And Sustainable Development, in which 24 papers were selected.

As a result, the authors found 100 benefits for sustainable development, which were further categorized into 54 advantages for the economic area, 25 for the social segment and 21 for environmental aspects. In this way, the results can help private companies understand the use of these technologies aimed at sustainable growth, plus bolstering the government to conduct public policies to encourage these practices in technology organizations.

As a practical implication, this study offers insight into the evolution of sustainable development. It enables the emergence of works that wish to explore the service sector, providing relevant information for decision-making and influencing managers and policymakers on the importance of applying Industry 4.0 toward the sustainability of the service sector and its applications.

The originality of this study lies in expanding the understanding generated by 4.0 technologies, by diverting attention from the manufacturing and agricultural sectors, which have abundant literature on the subject. With this, this work demonstrated that modern technologies have greater possibilities of an action directed at the service sector, in addition to being able to contribute to Sustainability 4.0 from the perspective of the sustainability tripod.

The purpose of this paper is to build a System Dynamics model to reveal the structure and dynamics of knowledge coupling affecting firms' innovation results in the digital context.

Drawing on the recombined view of innovation, this paper divides knowledge coupling into two dimensions: component knowledge coupling and architectural knowledge coupling. Then, the authors build a system dynamics model to identify the interaction of knowledge coupling factors and use the professional Vensim PLE to conduct simulation analysis to capture the dynamic interaction of motivation factors in knowledge coupling system.

The results show that both technology resources and digital dynamic capability play positive effects in the mechanism of knowledge coupling influencing firms' innovation results, while organizational inertia negatively affects the process of knowledge coupling to achieve innovation outcomes.

This study develops a holistic system dynamics model to reveal and elaborate on the complex dynamic mechanism of knowledge coupling impacting firms' innovation results in the context of digitization and provides a theoretical reference for companies to effectively adopt digital technology to carry out knowledge coupling strategy.

The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).

The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.

While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.

The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.

Successful adoption of building information modelling (BIM) by early adopters is crucial for its effective diffusion. The purpose of this study is to develop a framework of understanding that supports contextualized understanding of BIM adoption decisions in a BIM infant industry. The framework bridges the gap in current knowledge in terms of the absence of such a framework, which has hindered the structured understanding of the BIM decision of an adopter, curtailing the appropriate strategizing of their BIM adoption.

The study focuses on a BIM infant industry, where early adopters begin using BIM, allowing insights into this crucial initial stage of adoption. Identifying affordances as a versatile concept that could effectively represent not only what an adopter perceives and expects from BIM implementation, but also, what the adopter, in fact, can achieve from it, an affordance-led framework of understanding (AFU) was developed to comprehensively capture varying dynamics of BIM decision process. The study took a qualitative retroductive approach to theory with semi-structured interviews to gather necessary data from a sample of BIM adopters purposively selected to maximize the breadth and depth of data.

The study concludes by identifying and defining pertinent affordances as a new concept and a compulsory state for BIM adoption. Findings further demonstrate that existing theories can be linked to the AFU to strategically direct the affordances dynamics towards the pertinent state.

The AFU enables a deeper contextualizable view of innovation adoption that was absent in existing innovation studies. It significantly enhances the precision of strategizing BIM adoption compared to previous approaches, enabling adopters to plan and implement BIM in a manner that aligns well with their expectations and specific conditions.

The main research target of this paper is to capture the network effects using the case of mobile cellular telephony, identified in European telecommunication markets, and its determinants enhancing the process of digital technologies diffusion.

This research relies on panel and dynamic panel regression analysis. The empirical sample covers 30 European countries, and the period for the analysis is set for 2000–2019.

This work contributes by examining the network effects identified on European telecommunication markets that drive the process of digital technologies diffusion, but it also extends the understanding of the latter by tracing major determinants of fast network expansion, e.g. prices of access to and use of, per capita income, urbanisation, population density, accessibility of fixed telephony infrastructure. The main findings support the initial supposition that the installed base strongly enhances diffusion of new technologies, while other factors, for example, prices, are not of prime importance.

This research has certain managerial implications. The unveiled network effects driving adoption of technological innovations constitute a significant determinant of implementation of differentiation strategy by telecommunication companies. Due to network effects consumers' propensity to join the network is valued higher than the prices of services offered, which is crucial not only from the perspective of the company's pricing strategy but also enables telecommunication companies to introduce to the market new products and/or services concentrating on increasing its quality and usability rather than future prices.

This is the first work that empirically verifies the intercompanies and interpersonal diffusion of cellular telephony, hypothesising that this process relies on unique network effects.