Ali Alalwan

Abdullah M Baabdullah
email: baabdullah@kau.edu.sa

Nripendra P Rana
email: n.p.rana@swansea.ac.uk

Yogesh K Dwivedi
email: ykdwivedi@gmail.com

Fadia Hudaib

Ahmad Shammout
email: ahmad.b.shammout@gmail.com

Examining the Factors Affecting behavioural intention to Adopt Mobile Health in Jordan

Keywords: Mheath, Jordan, Adoption

Health organizations worldwide express a considerable attention to utilize Mobile technology applications to provide a better health services to their people. One of the most emerging apps in this regard is Mobile health (M-health). Large amount of efforts, money, and time have been invested to provide such innovative technology. Yet, the adoption rate of these systems is still low. Additionally, such system has never been examined over the Jordanian context. Thus, this study aims to test the most important factors that could shape the intention of Jordanian people to use Mhealth. Four factors: perceived usefulness, social influence, awareness, and innovativeness were proposed as key predictor of behavioural intention. Data was collected using convenience sample size of 365 and was analyzed using structural equation modelling. The main statistical findings supported the role of perceived usefulness, social influence, and innovativeness. More discussion will also be provided regarding the current study practical and theoretical implications.

Introduction

Mobile technology has been growing dramatically over the recent years either in terms of number of users or the range of applications and technical products and services provided (i.e. Mobile learning, Mobile commerce, Mobile banking, and Mobile healthcare) [START_REF] Shareef | Consumer Adoption of Mobile Banking Services: An Empirical Examination of Factors According to Adoption Stages[END_REF]. For instance, the number of mobile subscribers worldwide reached 4.77 billion in 2017 as stated by Statista (2018a). This represents a lot of opportunities for organizations from different sectors (i.e. government, education, banking, healthcare) to utilize such vehicles to deliver their services in an advanced and innovative way to their customers [START_REF] Shareef | Reformation of public service to meet citizens' needs as customers: Evaluating SMS as an alternative service delivery channel[END_REF][START_REF] Shareef | Consumer Adoption of Mobile Banking Services: An Empirical Examination of Factors According to Adoption Stages[END_REF]. In this regard, about 3.8 million apps that are presented in Android and about 2 million for Apple's App store (Statista, 2018b). Such applications have also been the focus of attention of health organizations to serve their patients and provide their services and information in an effective and modern channel saving the time and efforts of both health organizations and recipients of health services [START_REF] Shareef | Examining adoption behavior of mobile government[END_REF]. Indeed, one of the man reasons that enhance the current prosperity of mobile usage and acceptance is the huge interest to invest in mobile technology by health and medical organizations (Statista, 2018c). In this instance, according to the same report of Statista (2018c), the market size of Mhealth was about 21 billion dollars and this number is projected to increase to 60 billion dollars by ( 2020). This prevalence of M-health could be returned firstly to the ability of such system to enhance the quality of medical services provided; having more interactive communicative channel with recipients of health services; cutting cost; hindering the impact of time and place restrictions [START_REF] Shareef | Reformation of public service to meet citizens' needs as customers: Evaluating SMS as an alternative service delivery channel[END_REF][START_REF] Schnall | A user-centered model for designing consumer mobile health (mHealth) applications (apps)[END_REF]. Additionally, people increasingly have more health conscious and therefore, are more interested in adopting M-health applications [START_REF] Atallah | The Prevalence and Usage of Mobile Health Applications among Mental Health Patients in Saudi Arabia[END_REF][START_REF] Brown | Assessment of the Health IT Usability Evaluation Model (Health-ITUEM) for evaluating mobile health (mHealth) technology[END_REF]. Conceptually, M-health could be defined as a novel and new system empowered by using smart phones, personal digital assistants (PDAs), and any other mobile technology to attain a wide range of healthcare and preventive health services [START_REF] Singh | Mobile Health Applications: The Authors Reply[END_REF]. In Jordan, there is a recent interest in utilizing mobile facilities to provide and secure adequate level of healthcare services especially for residents of remote areas. For instance, a new project with cost of $1 million introduced by the Health Ministry of Jordan to serve about 10,000 people in the southern region is a "quantum leap (Jordan Times, 2015). However, permanent challenge for any new system like M-health is to convince people about the benefits of such system and accordingly motivate them to adopt it [START_REF] Alalwan | Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, perceived risk and self-efficacy[END_REF][START_REF] Lee | Determinants of adoption of mobile health services[END_REF]. Therefore, there is a need to discover and examine the main aspects that could shape the Jordanian people intention toward M-health care applications. Nevertheless, as a new and very novel technology in Jordan, the related issues of mobile health have not yet received attention from researchers in Jordan. Accordingly, this study aims to identify and examines the main factors that could predict the Jordanian intention to adopt Mhealthcare.

Theoretical Foundation

As discussed above, the adoption of M-health is the corner stone of the success of implementing such systems. Thus, a good number of studies that have recently attempts to explore and examine the main factors predicting the customers' intention and adoption (i.e. [START_REF] Dwivedi | A generalised adoption model for services: A cross-country comparison of mobile health (m-health)[END_REF]Hoqu and Sorwar, 2017;[START_REF] Lee | Determinants of adoption of mobile health services[END_REF]. Such of that [START_REF] Lee | Determinants of adoption of mobile health services[END_REF] identified four factors: usefulness, monetary value, convenience value, illness experience as key determinants of Intention to adopt Mhealth. Their statistical results largely supported the impact of usefulness, convenience value, and monetary value while illness experience did not have any impact in this regard. Extending the Unified Theory of Acceptance and Use of Technology (UTAUT2) was also formulated [START_REF] Dwivedi | A generalised adoption model for services: A cross-country comparison of mobile health (m-health)[END_REF] to predict the adoption of M-health. According to [START_REF] Dwivedi | A generalised adoption model for services: A cross-country comparison of mobile health (m-health)[END_REF], excluding hedonic motivation, the rest factors of UTAUT2 (performance expectancy, effort expectancy, facilitating conditions, social influence, price value) have a direct influence on intention to adopt M-health. Likewise, Hoqu and Sorwar (2017) propose their model base on UTAUT and technology anxiety and resistance to change. Their empirical findings supported the effect of effort expectancy, performance expectancy, social influence, technology anxiety, and resistance to change on the customers' intention to adopt M-health. Perceived value, perceived behavioural control, perceived physical condition, subjective norm, technology anxiety, and self-actualization need were tested by [START_REF] Deng | Comparison of the middle-aged and older users' adoption of mobile health services in China[END_REF]. [START_REF] Deng | Comparison of the middle-aged and older users' adoption of mobile health services in China[END_REF] also considered the moderation impact of age on the relationship between these predictors and intention to adopt M-health. Their practical results found out that the impact of these factors significantly different form older to middle-aged. Differently, Zhang et al. (2017) provided statistical evidences regarding the main obstacles (health habit, sunk cost, transition cost, and privacy concerns) that hinder the customer's willingness to adopt M-health. Even though, there is an international interest in testing the adoption of M-heath, in Jordan, there is not any study that has tested such issues. This, in turn, motivates this study to consider the Jordanian health sector as well as to identify the main factors that could shape the Jordanian individual intention to adopt M-health applications.

Conceptual Model and Research Hypotheses

As noticed in the previous studies, there are a number of factors such as performance expectancy, usefulness, and social influence. The importance of these factors have been repeated in different studies [START_REF] Alalwan | Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust[END_REF]Dwivedi et al., 2017a;[START_REF] Dwivedi | Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model[END_REF][START_REF] Dwivedi | A generalised adoption model for services: A cross-country comparison of mobile health (m-health)[END_REF]Hoqu and Sorwar, 2017;[START_REF] Lee | Determinants of adoption of mobile health services[END_REF]. Therefore, these factors namely: perceived usefulness and social influence were considered in the current study model. However, over the mobile technology literature, innovativeness and awareness have been largely validated as key predictors of customers intention to adopt Mobile technology (i.e. [START_REF] Kapoor | Empirical examination of the role of three sets of innovation attributes for determining adoption of IRCTC mobile ticketing service[END_REF][START_REF] Lu | Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology[END_REF][START_REF] Slade | Modeling consumers' adoption intentions of remote mobile payments in the United Kingdom: extending UTAUT with innovativeness, risk, and trust[END_REF]Lee and Son, 2017;[START_REF] Velmurugan | Consumers' awareness, perceived ease of use toward information technology adoption in 3G mobile phones' usages in India[END_REF]. Therefore, both innovativeness and awareness were considered in the current study model. It was also supposed that perceived usefulness could be predicted by both innovativeness and awareness. The proposed conceptual model and research hypothesises are presented below:

H1: Perceived usefulness will positively influence people intention to adopt Mhealth in Jordan. H2: Social influence will positively influence Jordanian people intention to adopt M-health. H3: Innovativeness will positively influence Jordanian people intention to adopt Mhealth. H4: Innovativeness will positively influence perceived usefulness of M-health. H5: Awareness will positively influence Jordanian people intention to adopt Mhealth.

H6: Awareness will positively influence perceived usefulness of M-health.

Research Methodology

A questionnaire survey was conducted to collect the required data from a convenience sample size of 600 Jordanian people. Those respondents were approached in several places at hospitals and medical centers in Jordan. Researchers firstly provided those respondents with a brief about the concept of M-health and their features and benefits. Then, the questionnaire was left with respondents to be completed. The main scale items of usefulness and behavioral intention was tested from scale proposed by [START_REF] Davis | User acceptance of computer technology: A comparison of two theoretical models[END_REF]. Social influence was tested using measure items from [START_REF] Venkatesh | Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology[END_REF]. A scale used by Aldás-Manzano et al. ( 2009) was considered to test Innovativeness while [START_REF] Rogers | Diffusion of innovations[END_REF] scale was adopted to examine awareness. Seven point Likert scale was employed to test these items. The questionnaire was converted to Arabic using back translation method suggested by [START_REF] Brislin | Comparative research methodology: Cross-cultural studies[END_REF]. A pilot study was also applied to for more sureness regarding factors reliability and validity. The results in this regard largely support all factors validity as well as Cronbach's alpha not less than 0.70 was recorded for all factors [START_REF] Nunnally | Psychometric theory[END_REF].

Results

Response Rate

Out of 600 questionnaires allocated, 365 that are returned and found to be valid for further analyses. The vast majority of respondents (41.6%) were noticed to be within age group of 25 to 35. About 52.6 percent of the current study participants were female where about 47.4% are male. Regarding the educational level, more than 70% of respondents hold a bachelor degree or above and have income level between 400 JOD and 800 JOD. Descriptive statistics also indicted that more than 93.2% have been using smart phones for more than 3 years.

Structural Equation Modeling Analyses (SEM)

Two stage method of SEM was applied using AMOS 21.0. Five factors (BI, USF, AW, SI, and INN) with their items are targeted in the first stage of SEM: measurement model. The revised version of the measurement model was noticed to be adequately fit the observed data as all fit indices were noticed within their acceptable level as follow: CMIN/DF was 2.874, GFI= 0.921, AGFI= 0.886, NFI= 0.932, CFI= 0.958 and RMSEA= 0.055 [START_REF] Hair | Multivariate data analysis: A global perspective[END_REF][START_REF] Byrne | Structural equation modeling with AMOS: Basic concepts, applications and programming[END_REF]. Both average variance extracted (AVE) and composite reliability (CR) were also examined and their results as presented in Table 1 existing withier their cut-off value (higher than 0.70 for CR and 0.60 for AVE). As seen in Table 1, the squared root of AVE for each construct was larger than the corresponding inter-constructs-correlation estimates, which in turn, supports the discriminant validity of the current study constructs. [START_REF] Hair | Multivariate data analysis: A global perspective[END_REF][START_REF] Byrne | Structural equation modeling with AMOS: Basic concepts, applications and programming[END_REF]. About 45% of variance was accounted in the behavioural intention to use Mobile health care applications and about 32% of variance in perceived usefulness. According the path coefficient analyses, innovativeness (γ=0.39, p<0.000) was the most powerful factor affecting Jordanian customer's intention to adopt Mobile healthcare applications followed by perceived usefulness (γ=0.22, p<0.000); and then social influence (γ=0.13, p<0.002). Yet, awareness does not reflect any variance in the behavioural intention (γ=0.03, p<0.966). Further, USF was found to be significantly predicted by the role of both innovativeness (γ=0.15 p<0.029); and awareness (γ=0.16<0.

20). 6 Discussion

As proposed in the current study introduction, this study attempts to provide further understanding regarding the main factors that could shape the Jordanian people perception and intention toward M-health. Thus, an empirical study was necessarily to be conducted. The main statistical results yielded largely supported the predictive validity of the current study model due to the fact that about 45% and 32% of variance was accounted in behavioural intention and perceived usefulness. This, in turn, supports the theoretical foundation proposed in the current study. Statistical results also supported the impacting role of innovativeness in contributing both perceived usefulness and behavioural intention. This means that those respondents who have a high degree of innovativeness are more likely to positively value the benefits and utilities of M-health as well as they are more likely to be motivated to adopt such system soon. This could be attributed to the fact that Mhealth as any other mobile technologies is more novel and pioneer system, and accordingly, it is a manifestation of modern life. Different Mobile technology studies that have addressed the role of innovativeness such as [START_REF] Lu | Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology[END_REF]; [START_REF] Slade | Modeling consumers' adoption intentions of remote mobile payments in the United Kingdom: extending UTAUT with innovativeness, risk, and trust[END_REF]; Lee and Son (2017). Perceived usefulness was the second strongest factor enhancing the behavioural intention to adopt M-health. As long as individuals perceived using M-health more efficient and productive than traditional way of attaining health services, they will be more motivated to adopt such services. In fact, Mobile technology and all related applications enjoy with high degree of Mobility, which in turns, empower individuals to access a wide range of services without time and place restrictions. As well as, Mhealth helps patients particularly to reduce waiting time of medical services and accordingly saving their time and efforts as well. Such results related to perceived usefulness are in the line with these studies that have supported the related area of Mhealth applications (i.e. [START_REF] Rana | Citizens' adoption of an electronic government system: towards a unified view[END_REF][START_REF] Lee | Determinants of adoption of mobile health services[END_REF][START_REF] Dwivedi | A generalised adoption model for services: A cross-country comparison of mobile health (m-health)[END_REF]. Statistical results have proved the role of social influence in predicting behavioral intention to adopt M-health. This means that people are more affected by the opinion and suggestions coming from their social system. Such results could be attributed to the fact that social system in Jordan positively look at the mobile applications overall and people would like to share and generalize their positive experience with such applications with their friends, colleagues, and relatives. From the other hand, Mhealth is very new and novel technology. Accordingly, individuals who do not have adequate experience and information to cope with such novel and new systems are more likely to be influenced by opinions and information coming from people surrounding them [START_REF] Venkatesh | Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology[END_REF]. Such results are compatible to other studies that have assured the role of social influence (i.e. [START_REF] Dwivedi | A generalised adoption model for services: A cross-country comparison of mobile health (m-health)[END_REF]Hoqu and Sorwar, 2017). Finally, even though there was not any effect for awareness on the behavioural intention, awareness is still very important factor in the current study model by it impact on the perceived usefulness. People who fully aware the main features of Mhealth and its associated benefits are more likely to perceive using such system as more productive and saving their time and efforts. This could be returned to increase health awareness and the importance of health technology among people in Jordan and worldwide. There is good number of studies (i.e. Kapoor et al., 2013;Vishwanath and Goldhaber, 2003;Ajili et al., 2012;Alsheikh and Bojei, 2014) that have supported the role of awareness in shaping the people perception toward new systems.

Theoretical and Practical Implications

Even though there is a growing interest in studying the related issues of M-health applications, this area still require further examination and explanation. Therefore, this study represents a good theoretical contribution by focusing more on the main aspects of M-health. In details, this study was successfully able to propose a solid theoretical model comprising a group of the most important factors (i.e. perceived usefulness and social influence). As well as, innovativeness and awareness have not been considered by prior M-health studies. Therefore, this study introduces another considerable contribution by expanding the current understanding regarding these factors. Further, the data was collected from 365 respondents and are analysed using SEM. By doing so, this study was successfully able to provide solid statistical evidence regarding the main factors predicting behavioural intention to adopt Mhealth. There are a few studies that have tested the adoption of M-health in developing countries. This is in addition to the fact that there is no study that has tested such technology in Jordan yet. Accordingly, This study represents a real contribution by expanding the current awareness and understanding regarding this phenomena in Jordan and developing countries as well.

From practical perspectives, a number of issues related to the current study findings have to be the focus of attention of M-heath service providers. Firstly, the significant role of usefulness should be taken into account. For instance, health organizations have to convince their target market about the benefits and utilities comprised in using M-heath such as less waiting time, less efforts, more convenience of time and location than traditional tools to attain the medical services. Organizations have also focus more in the novelty and newness of M-health along with the fact that using M-heath is a part of current modern life. This, in turn, will largely enhance the level of innovativeness existing in using M-health.

Limitations and Future Research Directions

There is a number of limitations that have to be addressed in the current study. Such as, convenience sampling was used in comparison with probability sampling method. This, in turn, reflects on the generalizability of the current study results. Further, this study only considers the behavioural intention while the actual use of M-health was nt tested. Thus, future studies could provide more accurate view about this area by considering the actual use behaviour. This study does not take into account the impact of resources and facilities required to use M-health, which in turn, represents an important of direction should be tested by future studies. The moderation effect of age and gender was not tested in the current study. Accordingly, these aspects have been the focus of attention of future studies. Finally, this study was conducted in Jordan, and accordingly, testing the related issues of M-health in different developing and developed countries could provide further understanding in this respect.

Figure 1 :

 1 Figure 1: Conceptual Model Adapted from Dwivedi et al. (2016); Lee and Son (2017); Velmurugan and Velmurugan (2014)

Table 1 : Constructs Reliability and Validity

 1 At the second stage of SEM, structural model was tested with six causal paths that are presented in the current study model. The fit indices of structural model were approved to have acceptable values as such CMIN/DF was 2.954, GFI= 0.913, AGFI= 0.854, NFI= 0.921, CFI= 0.95 and RMSEA= 0.058

		CR	AVE	SI	USF	INN	AW	BI
	SI	0.885	0.722 0.850
	USF 0.874	0.637 0.299 0.798
	INN 0.910	0.773 0.350 0.249 0.879
	AW	0.901	0.696 0.498 0.280 0.685 0.834
	BI	0.891	0.673 0.357 0.353 0.492 0.402 0.821

Table 2 : Results of Standardized Estimates of Structural Model

 2

	Hypothesized path	Estimate	S.E.	C.R.	P


Smart City and Green Development

Smart city is a strategy that aims at employing technology to improve life quality in urban areas. Among its main objectives, the environment quality is the top one. The EU vision on smart cities is strongly focused on energy efficiency, on nearly-zero energy buildings, on the reduction of CO2 emissions and so on. Therefore, some aspects of the smart city overlap with the idea of green city. Green city is an older but always updated vision, that aims at creating cities with a lower environmental impact, able to reduce the consumption of natural resources and to improve the quality of air and water.

This study is designed to understand if smart city and green city have similarities, to what extent they do overlap and how many synergies it is possible to create pursuing these two urban strategies at the same time. After a deep analysis of the international literature about these two subjects, we examined the portfolio of the initiatives that are usually employed, and we compared it with the international indicators related to the green city performances. We outlined overlapping areas and reached conclusions on the convergence of smart and green urban policies.

Introduction

Currently, the topics of green economy and sustainable growth are highly relevant, since the customers/consumers/citizens' sensitivity towards the environmental quality has increased. Economy and respect for the environment cannot and shouldn't be considered as opposing topics but rather as 'two sides of the same coin', as objectives to be both pursued in synergy and harmony [START_REF] Cutaia | Sostenibilità dei sistemi produttivi: strumenti e tecnologie verso la green economy[END_REF].

This theme is more keenly felt by cities: in fact, the continuous and strong dimensional growth of urban centres produces an exponential increase of the pollution and the consumption of energy and natural resources such as water.

Besides, cities are the place where people, students and enterprises are concentrated: cities have always been the place selected for the production of goods and services, for related marketing and consumption. They are also the place where the tourist flows are more and more directed: their demand increases the consumption of resources and can make unsustainable the unresolved concerns related to, for example, mobility and pollution [15].

Cities are meeting the new needs and requirements by means of strategies that can be defined digital, green, smart and sustainable. These four strategy fields do not coincide with each other but show strong overlapping areas.

•

The digital city is a city that largely employs ICT to convey data and information and to create bidirectional communication channels between citizens, institutions and enterprises.

•

The green city is a city that aims at developing infrastructures, spaces, facilities and urban activities with a low or even with no environmental impact.

•

The sustainable city is a city that aims at developing a socio-economical urban context able to balance economic development with respect for the environment and social equity.

•

The smart city is a city focusing on the use of technologies to improve life quality in urban areas. Overlaps and differences can be easily seen among these strategic policies for the city development. A local public transport system using advanced technology and ICT to reduce CO2 emissions and to provide a better service to all citizens, with a special attention to the most disadvantaged groups of people such as disabled, older people, mums with strollers, is at the same time digital, smart, green and sustainable. On the contrary, the increasing of urban parks is a green project only, the General Register Office digitisation is a digital project only, the efficiency raising in energy production in smart grid is (almost) exclusively smart, and so on.

The concept of smart city that has spread in recent years tends to take in high consideration the smart, green and digital aspects simultaneously [START_REF] Dameri | Searching for Smart City definition: a comprehensive proposal[END_REF]. This city development line is emerging thanks mainly to the European Union guidelines that combine the guidance with funds and financing for the research and the implementation of smart projects, and it ends up prevail vs. other interpretations of smart city [START_REF]Network, Smart and Open: Three Keywords for Information Systems Innovation[END_REF][START_REF] Ahvenniemi | What are the differences between sustainable and smart cities?[END_REF].

Actually, the concept of smart city, both in academic definitions and practical implementations, takes on much wider and more heterogeneous meanings and contents and, drawing its perimeter seems quite difficult. Nevertheless, in the smart programs of the cities, the concern for the environment constantly appears as a core element.

Therefore, the research question is the following: which is the relation between green city and smart city? Are there common dimensions (and then indicators related to each dimension)? Is it possible to design policies that concur to the achievement of such common objectives?

Smart, digital, green e sustainable 2.1 The origin of the concept of smart city

The branch of research and government named smart city is today among the main strategies not only of cities but also of global member states and organizations such as UN, OECD, European Union. Cities have started many smart initiatives, and just as many are the European programs financing such initiatives and the reports, studies and researches of national and supranational bodies on this subject. However, the definition of smart city is not yet univocal or consolidated [START_REF] Nam | Conceptualizing smart city with dimensions of technology, people, and institutions[END_REF].

The main reason of this indeterminacy lays in the process that led to the success of the so-called smart initiatives. Often a bottom-up driven process, namely driven by isolated initiatives of citizens and enterprises; a process that started in territories, in the urban areas of some pilot cities and then has spread worldwide [START_REF] Caragliu | Smart cities in Europe[END_REF]. 2011). To understand what a smart city is, it is first of all necessary to carry out three types of analysis:

•

The historical analysis, studying how the topic has started and developed and in which time frame;

•

The territorial analysis, exploring the coming up of smart experiences, researches or policies in urban areas and in the regions of the world, examining also how the phenomenon started and progressively spread itself; •

The terminology and content analysis that compares the different terms used to identify the cities that started a path for the improvement of the living conditions in their territories, thanks to the more or less intense use of advanced technologies such asbut not onlythe ICT and the minimisation of environmental impact of the cities.

The historical analysis highlights how the smart city has far-off roots and how it constantly intertwines with the concept of digital city [START_REF] Dameri | Defining an evaluation framework for digital cities implementation[END_REF].

The historical analysis is a first distinctive element between digital city and smart city, that underlines the different development that the two experiences had in the past twenty years. Other relevant differences emerge from the analysis of territorial and content elements of these two smart city metaphors. The review of existing literature allows us to draw the most quoted definitions of digital city and smart city. By reading and interpreting them, some aspects become immediately clear, some of them can be deducted from the digital or smart name of the city.

The digital city is strictly related to the use of information technology and especially to some of its implementations such as Internet, broadband and fast Internet connections at urban areas level, the use of mobile access devices, not only the traditional PC, but especially, the so called smart devices (and here it is the first source of terminology confusion) such as smart-phones and tablets.

Among related key topics we find broadband and connectivity, that make the digital city also a wired city or a network city [START_REF] Cocchia | Smart and digital city: A systematic literature review[END_REF], the use of open data structures, thanks to which public information is accessible and available to everyone and this make the digital city also an information city [START_REF] Anthopoulos | Smart utopia VS smart reality: Learning by experience from 10 smart city cases[END_REF]; the creation of digital services offered to citizens both by public bodies and by private enterprises and organizations [START_REF] Cleland | The 'engage'System: Using Real-Time Digital Technologies to Support Citizen-Centred Design in Government[END_REF]; the virtualization of spaces, behaviours and relationships that lead to the creation of a sort of virtual city overlapping the real one, with its own rules, behaviours, relationships etc. This makes a digital city also a virtual city or an ubiquitous city [19; 2].

The definitions of digital city do not talk of quality of life explicitly, but they show that the process of transformation of the city generated by digitisation policies is fully oriented towards the citizen and his needs. And indeed, one of the main obstacles to the full realization of the digital city is mainly the digital divide, which separates those who have the skills to access digital information and services from those who haven't, creating a form of virtual exclusion [START_REF]Good Govemance far Digital Po/icies: How to Get the Most Out of ICT: The Case of Spain's Pian Avanza[END_REF]. Exclusion not only in terms of fruition, but also in terms of offer, with some enterprises and public bodies that are able to offer digital information and services and others that do not have the knowledge and the skills to do so and remain excluded from the implementation of the digital city and from related appropriation of returns.

The analysis of the main definitions of smart city, highlights the primary characteristics of what a smart city should be. A first reading of the definitions suggests, in the first place, that the concept of smart city is much more indefinite than the digital city one. As a matter of fact, some definitions are impalpable and identify the smart city just as a city able to create good living conditions for its citizens, regardless of how it manages to do that and of what tools or technology are used [START_REF] Giffinger | Smart Cities: Ranking of European medium-sized cities[END_REF]. Some definitions recall the digital city, recognising in those previous and more mature experiences a basis or a part of the smart city [START_REF] Caragliu | Smart cities in Europe[END_REF]. Other definitions are more concrete and refer to smart initiatives, infrastructures and activities mainly connected to some key elements of living in the city such as public transport, energy production and consumption, pollution and environmental impact of buildings and human or productive activities [START_REF] Dameri | Searching for Smart City definition: a comprehensive proposal[END_REF].

Actually, the main academic definitions of smart city are not able to represent what the smart city really is in the mind of those whoin municipal Governments, enterprises and University Departments are involved in its design and realization. A more practical vision can be extrapolated from the reports of the major technological players, IBM, Oracle or Microsoft for example, or of the big research centres such as Gartner and the Stanford University, or even more from visiting the websites of the several Italian, European or global cities that have taken the path of smartness. The analysis carried out enabled us to understand that there are some common themes that can be found both in academic studies and in the empirical implementations of the smart city.

The main topic, shared by all the sources we analysed, regards the negative environmental impact of cities and the need of containing or reducing it, especially through the reduction of CO2 but also through waste treatment, water quality etc. As a function of the relationship between city and environment, the smart city focuses on the enormous amount of energy used by the city, due to its residential and productive settlements and to the premises of enterprises, places of study and work, public bodies and, therefore, the need, on the one hand, of reducing the energy requirements and, on the other hand, of producing energy from clean and renewable sources. A smart city is not such if it does not make a wide use of the most innovative technology. Central is the key role of technology in the pursuit of all the smart city objectives and of the technology-based orientation of smart strategies, as well as the technologic, economic and social innovation that envisages in the smart city also a place of economic development with high added value and with a high content of technology and knowledge [START_REF] Zhuhadar | The next wave of innovation-Review of smart cities intelligent operation systems[END_REF].

A theme partly included in the smart city concerns the so-called smart community; in fact, it is an evolution of the digital city that aims at connecting citizens, at making available open access to online information and at the fruition of digital services also with mobile devices. The topic of smart community draws the attention on the role of citizens and on their active involvement in city smartness projects. Finally, even the macro-objectives of the smart city (at a general level) are homogeneous: the smart city aims at the citizens' well-being; a tangible well-being, based on ease of access to services and infrastructures, on economical well-being, on participation and social inclusion. A well-being built on the contrast to the typical inconveniences deriving from living in a city, such as traffic, pollution, congestion of public or private transport , and on the study of innovative solutions to limit such inconveniences. According to this last and wider meaning, the smart city becomes a city able to carry out a positive role for its residents and visitors, regardless of the devices used to achieve the smartness objectives.

From smart to green

The study and analysis of the materials collected and described in the previous paragraph allows us to highlight two concepts of smart city. The first one could be defined as wide: according to it the smart city is an intelligent city creating excellent living conditions for all its citizens. The purpose of this concept is to emphasize how nowadays the quality of life strongly passes through cities, urban areas, through the activities taking place there and the ability of local policies to achieve good living conditions, that are often hindered by the eccessive dimensions of cities and by their complexity.

The second concept, the more interesting one for our study, just defines the smart city as a subset of the successful city, that includes some issues such as infrastructures, energy, environmental impact, use of ICT; and where technology and innovation have a key role; all this is aimed at improving the quality of life in urban spaces and to attracting smart, innovative and fully developed persons and enterprises there.

According to this better focused meaning, the smart city actually takes on its own features, where technology, respect for the environment, use of ICT, applied to the physical elements of life in the city such as buildings and public transport, but also the virtual elements of urban life such as the need of receiving digital services or to accessing online information, are key elements to define a development path that is both sustainable and inclusive. According to this meaning, the smart city becomes partly green city, namely green city respectful of the environment, partly sustainable city, a city that defines paths of socio-economical development able to guarantee economic well-being, social inclusion and environmental quality to those living within its boundaries, not necessarily administrative ones but within the city area of influence.

Beyond definitions, the main difference between green city and sustainable city is not only the time frame: in the green city it is based on the present, in the sustaible city it is inter-temporal and through present and future generations. The main difference is that the sustainable city aims to reconcile environment, economy and social inclusion, stating that the respect for the environment and the sustainable use of natural resources are not in contrast with the economic wellbeing and the creation of value by enterprises and that the sustainable development has to aim at creating a balanced wealth also with regard to its distribution, avoiding the concentration of wealth in the hands of a few to the detriment of the economic and social inclusion of many. A sustainable city is also a fair city that aims at guaranteeing the internal well-being for everyone, no one excluded.

From the comparison between sustainable and smart city, we notice some overlapping elements between the two concepts. The main ones are the environment impact and the use of natural resources: they are present both in the sustainable city and in the smart city. Both these two ideas of city consider the economic development as a key element of urban life that, for the sustainable city, should be reconciled with the natural environment, whilst in the smart the smartness is even a source of sustainable economic growth. Citizens play a central role but is intended in two different ways: in the sustainable city it primarily pursues the aims of equity among people and generations in the distribution of economic and natural resources, whilst the smart city directs its efforts towards the quality of life in urban areas. The social inclusion is a topic that has been added only in recent times and, however, in a marginal and indefinite way.

What certainly distinguishes the smart city from the sustainable one is the key role played by technology and, in particular, by ICT and by the most innovative ad advanced technologies in the realization of smart, quality and attractive cities, where people can live well, and where it is possible to achieve a widespread well-being and to combat social exclusion.

When they started to talk about sustainable economy and cities, the information technologies were still in a pre-Internet phase and confined in large enterprises and organisations; the pervasiveness of ICT in daily life of SME and citizens was still far away. Also the dimensions of cities were more contained, megalopolis could be countend on the fingers of one hand and the psychological threshold of the 50% of the world population that goes to live in cities was not overcome yet. These elements modified the metaphore of city, but they did not reduce the awareness of how urgent it is to answer to the needs of life in urban areas, to environmental decay, to the use of energy sources, mainly in cities, that from the Middle Ages to the present days, have been, and increasingly will be, the focus of economic and social life.

Green and smart city: a comparison of dimensions and indicators

Dimensions and indicators of the green city

Within the framework of general policies aimed at pursuing a green vision for urban agglomerations, first we can refer to OECD contributions. In particular, the topic of the green growth of the Oecd Declaration on Green Growth, of June 2009, was subsequently taken up and contextualised in the Green Cities Programme. This program aims at evaluating how much the urban green growth and the policies for sustainability can contribute to improving both the economic context and the environmental quality of metropolitan areas and, consequently, to increase the contribution of such areas to the national growth, to life quality and to competitiveness. In particular, the Green Growth Strategy identifies and promotes the activities necessary to reduce the environmental impact as potential sources of growth and refers to the need of internalise the negative environmental externalities. In these contributions, the green growth is intended to harmonise economic growth and environmental sustainability. As such, it only partially coincide with the concept of sustainable development since it focuses on economic efficiency and environmental protection that are only two of the three pillars of the sustaible development (that, as is known, includes also social equity and justice). The effort and the wish is that the social interests be integrated in the commitment for green growth [START_REF] Hammer | Cities and Green Growth: A Conceptual Framework[END_REF].

Urban green growth especially focuses on economic growth and on development through urban activities able to limit the negative environmental externalities and the impact of natural resources and environmental services [START_REF] Oecd | Green Growth in Cities[END_REF]. In fact, it is evident that the urban agglomeration significantly affects, mainly in new fast-growing metropolises (i.e. in the Far East), traffic congestion, pollution and the impact on the ecosystem and, hence, on the natural resources. The dimensions of the green city can be expressed in a series of indicators, many of which have given rise to the need of synthesize the different suggested variables in a single code.

Concluding this first part focused on dimensions and indicators of the green city, we can state the following:

•

The suggested dimensions cover the traditional areas of environmental protection: water, air, earth (more in general, non-renewable resources), waste management and energy, as well as human activities strongly affecting these resources: urban mobility, waste and buildings management. However it is evident that, for example, urban mobility is strictly connected to the quality of air and can generate separate assessments of the interconnected and interdependent indicators;

•

The suggested indicators are sometimes already operationalized, i.e. expressed as variables. The schemes propose then mixed (and therefore inconsistent) sets of indicators and variables; • No indexes are built with the suggested variables: the task of synthetizing the multiplicity of variables and identifying a form of synthetic evaluation is left to the researcher who adopts the scheme. It follows that the above is an interesting contribution to a more accurate and articulated knowledge of the green dimensions of a city, but it is not yet a valid tool for the measurement of the urban realities performance: the conceptual framework seems in fact to leave aside the definition of the strategic objectives of each specific city to which evaluations and measurements should necessarily and strictly be connected.

According to this framework and to the purposes of this study, it is evident the need of having at least one set of dimensions to be able to evaluate how smart initiatives can be qualified also as initiatives pursuing the green objectives of a city. Based on our findings, we suggest the following dimensions of a green city:

Dimensions and indicators of the smart city

As we have seen, the relevant definitions are not univocal. In the first place because the city smartness is a process and, as such, continuously changing and evolving. Besides, the main object on which the process takes place, i.e. the city, shows some typical characters as well as a multiplicity of different connotations (dimension, localisation, resources, socioeconomic and political context, etc.) that make difficult and especially, in our opinion, not very useful, any attempt of referring to "a unit". It is certainly more functional to our purposes to identify which are the city dimensions that come into play in the context of a smart approach. We therefore intend to focus on two scientific contributions identifying those that should be the main characteristics of smart cities, the significant dimensions of their development that, consequently, identify the indicators pertinent to each dimension.

With this regard, we refer to Giffinger et al. ( 2007) who stated that the smart city is "a city well performing in a forward-looking way in economy, people, governance, mobility, environment, and living, built on the smart combination of activities of self-decisive, independent and aware citizens". This approach not only considers the technology and digitalisation of structures and services (digital city) essential, but contemplates them in a project of improvement of life quality and in a wise management of resources, mainly natural ones (green city), through a participative governance (smart city). For this vision of city, the study identifies six areas of intervention whose design and management should be carried out in an intelligent perspective, built according to available resources and knowledge and with the active participation of independent and aware citizens. Every city can be defined as smart to the extent it is commited in the realization of:

• smart economy: competitiveness • smart environment: natural resources • smart governance: participation • smart living: quality of life • smart mobility: transport and ICT • smart people: social and human capital. Such dimensions are declined in 31 factors that make up the framework for the identification of indicators and the consequent evaluation of the performances of a smart city. In particular, this means to assess and measure aspects such as: entrepreneurial spirit, economic image, productivity, flexibility of labour market (that fall within the smart economy), environmental protection, pollution, sustainable management of resources (smart environment), partipation in decision-making processes, public and social services, transparent governance (smart governance), individual safety, cultural and educational structures, touristic attractiveness, social cohesion (smart living), accessibility, availability of ICT infrastructures, sustainable, innovative and safe transport systems (smart mobility), continuous professional training, flexibility and creativity, mind and cultural openness (smart people).

The results provided by the adoption of such framework are undoubtedly interesting since they allow to highlight the best city performances, also with respect to specific issues.

It is interesting to remember the ranking of the Smart City lndex carried out by the consulting company Between on 116 Italian chief municipalities on the basis of thematic areas. This index is not aimed at measuring the absolute level of smart innovation but the distance between the best city (score=100) and the others [START_REF] Between | Smart City lndex-Confrontarsi per diventare smart[END_REF]. The analyzed dimensions are the following:

• broad band indicators representing a particularly innovative contribution for the identified areas and for the adopted measurements. Besides, it is interesting to notice that the adopted meaning of smart city first of all requires that it may be possible to observe a substantial difference between a "before" and a "after", that such changes derive from a path pursued and contextualizable in a clear vision but, above all, that such changes have a strong connotation of innovation, "tangible" and "widespread" within the city.

The contributions of Giffinger et al. ( 2007) and Between (2013) however point out the typical limits of rankings: they are a "photograph" of the situation of a group of cities providing a synthetic vision of a complex phenomenon but they do not satisfy the need of an articulated and specific knowledge. In fact, many characteristics of the smart city are analysed in dychotomous key only or otherwise different weights are assumed (discretional) or, again, are adopted wide or limited visions of a same dimension characterizing a smart city. The reason of these limits is clearly, because the definition of smart city is not univocal and the measurement of the performances of the cities that have started integrated projects are still scarce. The dimensions and indicators suggested by such contributions can however be a valid support for the evaluation of the policies to be included in order to identify if and to what extent they are consistent with the dimensions a smart city should have.

A significantly different approach is offered by the Siemens' Efficient Cities study carried out by Cittalia that aims at analyzing a macro group of 54 mediumlarge cities based on their infrastructural allocations [START_REF] Siemens | EfficienCITIES.Città-modello per lo sviluppo del Paese, Cittalia. Siemens-Economist lntelligence Unit[END_REF]. The examined areas were urban environment quality, real estate assets, sustainable mobility and logistics, renewable energy, healthcare. The final result is the identification of six homogeneous groups of similar cities in which the different areas combine themselves bringing out one or more components: the cities of the environment, of the well-being, ideal cities, cities of the good living and of mobility, cities under development, of the energy.

Our interest for this study is based on its attempt to provide a richer and deeper, and then complete, knowledge of the city, through a multi-level classification: an initial level, based on factor analysis in main components (PCA) and a final one based on cluster analysis.

On the basis of a careful analysys of the doctrin' different contributions about the dimensions that should characterise green and smart cities, it emerges that the environment and energy topics are always present, though with different extent and importance, within the smart city concept and dimensions. As concerns the concept of green city examined in the first part, the illustrated contributions highlight in fact how the smartness of a city may not disregard a vision that considers essential the safeguard of natural resources, above all the non-renewable ones, the reduction of the environment impacts caused by human activities and enterprises processes, energy efficiency, and safety. This vision seems to include, or at least to overlap significantly, the green city concept with the smart city one.

Italian Smart City

Some Italian cities are an interesting, often mentioned, case of city planning and transformation according to a smart vision that began in 2010. The underlying vision, shared with stakeholders, is based on the way the term smart city is intended: "The Smart City improves the living quality through a sustainable economic development, based on research, innovation, technology and driven by the local leadership in a process of integrated planning ".

The annual report examined was carried out by FPA in order to photograph the situation of Italian cities on their path to become "smart", that is to say nearer to citizens' need, more inclusive, more livable. FPA identified and analysed 15 urban dimensions that, in the national and international context, set out the objectives for the cities (poverty, education, air and water, energy, economic development, occupation, tourism and culture, research and innovation, digital transformation and transparency, sustainable mobility, waste, public green, soil and territory, legality and security, governance). (ICITY RATE 2017) The set of these initiatives shows the participation of a large number of players: public subjects, private companies and citizens. The analysis, based on the description of the action and of the estimated result, provided a classification of the initiatives according to 5 dimensions among the ones suggested above: air quality, land use and consumption, energy consumption (efficiency raising, alternative and renewable energies), waste production and management, mobility, transport and logistics. As shown in Table 69 initiatives currently developed as smart (equal to the 68% of the total) show aspects that define them as green initiatives. Compared to the dimensions identified, the actions connected to the energy topic (containment of energy consumption, reconversion to alternative or renewable energies, etc.) show a higher frequency. Several are the initiatives connected to mobility, transport and logistics, too: many of which are classified also in the topic area "air quality and reduction in CO2 emissions".

Number

of smart actions Air quality 7 Soil use and consumption 6 Energy consumption 18 Waste production and management 2 Mobility, transport and logistics 14 GREEN IMPACT 47 In the examined case, it is clear that the characteristics and factors of the smart city show areas of evident overlapping with those of the green city as well as areas that are only partially common.

Conclusions

The smart city topic is gaining a position of great interest and newness for public administrations but also for the research community and for enterprises. The literature analysis highlights how the smart city concept does not have an accredited and fully shared definition yet. This is mainly due to a process of bottom-up type implementation of the smart city: local administrations, enterprises and associations moved independently to carry out smart small actions or large projects, often without a direction or planning able to define vision, strategies, goals and contents of the smart city. The definitions are based on the collection of experiences under a unifying hat, trying to keep together a multiplicity of aspects sometimes very different one from the other.

On the contrary, the green city has older origins and a better-defined perimeter. Provided that the city is a huge agglomerate -larger and larger from the geographical and population points of viewthat consumes natural resources and produces pollution, the green city is a urban planning strategy that tries to make the city greener thanks to public actions and single citizens behaviours aimed at the respect of the environment, that, at the same time, allows to its residents and visitors to enjoy healthier urban spaces.

The purpose of the Research questions of the study was to understand if there are relationships between smart city and green city, which are these relationships and how these two urban strategies can be directed towards this goal taking advantage of positive synergies. The analysis of the scientific literature, of national, international and local experiences on the smart city topic highlights that, among the several themes falling in the smart city perimeter, the environmental policies have a key role. This generates a partial overlapping between smart city and green city this does not mean that the two urban strategies fully coincide, nor that the green city can be considered as a subset of the smart city, because several are the differences that we can find in literature and in the analysis of empirical cases.

The key element that characterizes the smart city is technology, be it Information Technology or other engineering technologies applied to typical infrastructures of the urban fabric, such as roads, buildings, public lighting, transport, etc. On the contrary, the green city key element is the environment and its protection in every possible meaning of the word. The protection of the environment is also the clear objective of the green city, whilst the smart city has a much wider, ambitious but vague objective, that is to say, to improve the quality of life in the urban context. By intertwining above key elements and objectives, we can identify the overlappings between smart city and digital city. If we want to define such overlapping, we could say that smart city and digital city coincide where technology is employed to reduce the city impact on the use of natural resources, on energy consumption and soil, on air and water pollution.

In the above overlapping, it is possible to identify common dimensions, shared indicators and synergic policies to go towards a city that is both smart and green. In fact, the common dimensions are exactly those on which technology can intervene on taking positive actions on these green topics: air quality, soil use and consumption, energy consumption, waste management, logistic mobility and urban transport. The common indicators are those that aim at measuring the green impact obtained by smart actions, namely activities for the environment protection that employ innovative technologies. Let us think about the use of ICT to offer remote services and to avoid unnecessary travels the use of technologies for the production of energy from clean and renewable energy sources, the increase of energy efficiency of buildings, and so on.

We should keep in mind that not all the smart actions are also green and the other way round: it is therefore up to each city to determine what are its smart objectives, its green objectives and to identify overlappings and synergies to be supported with appropriate political, administrative and design measures. The specificity of the choices of every single city, though included in a smart/green overall vision common to other cities, clearly stands out from the empirical analysis of the report.

In the report, it is evident that the smart actions and projects were born in the absence of a well-outlined strategic framework and of definite objectives: this does not allow either to apply prioritization criteria among the actions to be carried out, or to measure and evaluate the achieved results. It follows that in the smart perimeter is included a really too wide and heterogeneous range of actions very different one from the other and lacking shared objectives.

Besides, the detailed analysis of all smart actions and projects of the report highlights how, mainly as regards European projects, the overlapping of smart and green strategies is very high. We should consider the following: the European projects are guided by strategic guidelines of the European Union, that tends to attribute to the smart city concept a much greener content than that emerging from the literature.

Overall, regarding the smart projects highlighted in the report, it also emerges that the energy component is predominant. Here we have to make another consideration: smart cities, thanks to the technological component, are a topic that strongly involves also the hi-tech sector companies that are particularly interested in the smart city as a potential market for their technological products. From the analysis of Genoa case, it comes into light that, lacking the city its own strategic vision, the choices of priority areas were heavily influenced by two forces: the areas where the European Union placed funds and the interest of partner companies of the Smart Cities.

In conclusion, both the literature analysis and the study of an empiric case allowed highlighting that a large shared area (Research question 1) exists between smart city and green city, whose dimension is influenced by the choices and priorities of each city with respect to the green objectives that can be achieved by using smart technologies. The dimensions of this overlapping regard the use of natural resources, energy consumption and polluting emissions (Research question 2). The smartness and greenness indicators of the city have to be applied considering that not all the smart activities have green impacts, and not all green actions are also smart, so that an indicator such as the reduction of CO2 emissions should be interpreted in relation with the actions that generated it (Research question 3). Lastly, as regards the policies common to the smart city and green city strategies (Research question 4), relevant synergies are depending on the choices and on the vision of each city. It is up to each city to choose if and to what extent to be smart or green and if to pursue the green objectives through technology, citizens' virtuous behaviour or both.


Salma S Abed

A critical review of empirical research examining SMEs adoption from selected journals

Keywords: Technology adoption, SMEs, TOE, Empirical Research

The purpose of this paper is to review the literature on empirical research examined Small and Medium size Enterprises (SMEs) from selected journals. This has been achieved by reviewing the most examined constructs to identify the key significant factors in the literature. The selected research papers for reviewing are accessed from only high-ranking journals. The review addressed technology adoption in the context of SMEs. The paper attempts to review the studies based on technology-organisation-environment (TOE) framework to identify the relevant set of variables for technology adoption in SMEs. The most significant factors found to be relative advantage and compatibility from the technological context, top management support and size from the organizational context, and external pressure from the Environmental context. This review intended to guide future researchers to improve the predictive power of their examined models.

Introduction

Small and Medium Enterprises (SMEs) are considered one of most significant sectors to promote nations financial and economic growth [START_REF] Abed | Social Commerce as a Business Tool in Saudi Arabia's SMEs[END_REF]. SMEs are defined based on their employment and economy figures as well as fixed assets and sales volumes. They typically employ less than 500 workers. They are known for their major advantages including employment creation at low capital cost, flexibility, and innovation [START_REF] Abed | SMEs' adoption of e-commerce using social media in a Saudi Arabian context: a systematic literature review[END_REF][START_REF] Ramdani | Knowledge management and enterprise systems adoption by SMEs: Predicting SMEs' adoption of enterprise systems[END_REF][START_REF] Sunday | Examining Information Communication Technology (ICT) Adoption In SMEs: A Dynamic Capabilities Approach[END_REF]. Economies of most OCED nations comprise nearly 96% to 99% of small and medium enterprises that account for 80% economic growth for those nations. Their existence is evident in all developed and developing countries to the extent that GDPs for North American and European countries today is contributed significantly by SMEs with 99% of all businesses. Apart from that, around 70% job creation is credited to this sector [START_REF] Scupola | SMEs' e-commerce adoption: Perspectives from Denmark and Australia[END_REF]. SMEs are known for their significant role in driving the economic growth. Governments of emerging nations and developed countries support SMEs sector through encouraging public policies [START_REF] Abed | Social Commerce as a Business Tool in Saudi Arabia's SMEs[END_REF]. Large corporations, that normally play their central role in country's formal economy, could not effectively operate in absence of SMEs [START_REF] Abed | Social media as a bridge to e-commerce adoption in SMEs: a systematic literature review[END_REF]. In fact, they appear more leading where there's a need to rely less on traditional resources and effectively support technology and human intellectual capital as they depends on innovation, change adoption, creation of information and knowledge through strategic disposition of knowledge capital [START_REF] Abed | Social Commerce as a Business Tool in Saudi Arabia's SMEs[END_REF][START_REF] Ajmal | Critical success factors influencing e-commerce adoption in SMEs: A review and model[END_REF][START_REF] Scupola | SMEs' e-commerce adoption: Perspectives from Denmark and Australia[END_REF].

The existence and growth of SMEs sustain through inter-organizational integration and access to knowledge for which SMEs significantly need resources including Information technology, networking, internet and social media, configurable platforms, and prompt data processing models [START_REF] Abed | SMEs' adoption of e-commerce using social media in a Saudi Arabian context: a systematic literature review[END_REF]. Such resources, especially information and communications technology enable SMEs to operate cost-effectively, both at national and international levels [START_REF] Ajmal | Critical success factors influencing e-commerce adoption in SMEs: A review and model[END_REF]. They need to earn and maintain competitive advantage through improved service quality and product expansion, customer evaluations, improved effectiveness and efficiency, cost reduction, and sales forecasting.

Research studies show that SMEs profit heavily by ICT in order to achieve sustainable growth in developed economies [START_REF] Orser | The influence of gender on the adoption of technology among SMEs[END_REF][START_REF] Widyastuti | Benefits And Challenges Of Cloud Computing Technology Adoption In Small And Medium Enterprises (SMEs). Bandung Creative Movement[END_REF]. The beginning of last decade observed a huge increase in the use of online platforms by businesses in the US and Europe. It showed similar growth in other parts of the world where online business ventures added billions to aggregate revenues [START_REF] Abed | Social Commerce as a Business Tool in Saudi Arabia's SMEs[END_REF]. Certain factors, however, affect SMEs' economic development and weaken their access to global markets, including ICT adoption. This adoption of ICT by SMEs is yet to be explored fully. This study will review the literature based on the TOE framework constructs in order to identify relevant set of variables for technology adoption in SMEs.

Technology adoption

Technology adoption is defined as the choice to obtain and use a new innovation [START_REF] Ghobakhloo | The role of owner/manager in adoption of electronic commerce in small businesses: The case of developing countries[END_REF]. The mental acceptance of a technology by an individual or an organization, and the decision, by an individual or organization, to implement and utilize a technology [START_REF] Williams | The unified theory of acceptance and use of technology (UTAUT): a literature review[END_REF]. Various models and theories have effectively explained technology adoption as voluntary individual behavior including; TAM, IDT, TRA, TRB, TOE, and UTAUT proposed by [START_REF] Davis | Perceived usefulness, perceived ease of use, and user acceptance of information technology[END_REF], [START_REF] Rogers | Diffusion of innovations[END_REF], [START_REF] Fishbein | Belief, attitude, intention and behaviour: An introduction to theory and research[END_REF], [START_REF] Ajzen | The theory of planned behaviour[END_REF], [START_REF] Tornatzky | The process of technology innovation[END_REF] and [START_REF] Venkatesh | User Acceptance of Information Technology: Toward a Unified View[END_REF] respectively. This technology adoption was categorized at three distinct levels: organization, group, and team [START_REF] Ghobakhloo | The role of owner/manager in adoption of electronic commerce in small businesses: The case of developing countries[END_REF]. However, some studies show that TRA, TRB, and UTAUT are more aimed at forecasting individual adoption as compared to organizational context. In contrast, the TOE frameworks are mostly used at the organizational level to analyse the technology adoption. In recent years, the TOE frameworks have gained significant value among several authors who employ them to gain theoretical perspective on the ICT adoption as well as to test its variables for acceptance of new technologies [START_REF] Zhu | Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors[END_REF].

Even though IDT and TOE framework constructs are suitable for examining organizational adoption, TOE frameworks are given more weight due to their addition of new construct (i.e. environmental) in explaining the technology adoption. [START_REF] Zhu | Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors[END_REF] found TOE framework having more significance than the IDT in their theoretical evaluations. As a result, this research study will consider organization-based research studies established on TOE due to their high significance over other frameworks. [START_REF] Tornatzky | The process of technology innovation[END_REF] initially developed the TOE framework in order to analyse the organizational-level adoption of a number of information technology products and services. Since then, TOE frameworks have emerged as significant theoretical perspectives by potential researchers studying technology adoption. The addition of various distinct variables including technological, organizational, and environmental in TOE framework has supplemented researchers to test and validate its advantage over other adoption models w.r.t. their ability to technology use, technology adoption, and value created by SMEs sector as a result of technology creation [START_REF] Ghobakhloo | The role of owner/manager in adoption of electronic commerce in small businesses: The case of developing countries[END_REF][START_REF] Ramdani | Knowledge management and enterprise systems adoption by SMEs: Predicting SMEs' adoption of enterprise systems[END_REF]. Therefore, there are many reasons to employ the TOE framework due to its many benefits including; its user adoption of ICT, its influence over value chain undertakings, its implementation, its diffusion among organizations after the adoption, foreseeing obstacles, its ability to develop better organizational competencies using the technology, and other factors impacting business decisions related to innovation-adoption. All three contexts of TOE framework, as explained by [START_REF] Tornatzky | The process of technology innovation[END_REF] influence the technological innovation adoption of the framework and its implementation. The following sections briefly outline those three contexts of Technological, Organizational, Environmental (TOE) framework; Technological Context: According to [START_REF] Claycomba | Predicting the level of B2B e-commerce in industrial organizations[END_REF], technological context is set of those variables that shadow their influence over individuals, organizations, and industries in their process of adopting innovations. [START_REF] Dedrick | Why firms adopt open source platforms: A grounded theory of innovation and standards adoption[END_REF] Further divided it into five innovation attributes that influence the possibility of adoption. A deep insight into technological context reveals that the adoption relies on various technologies, both inside and outside the organization. Moreover, it depends on application's apparent relative advantage, complexity in terms of learning curve, observability (imagination), compatibility (organizational as well as technical), and trialability (experimentation).

TOE Framework

Organizational Context: organizational context comprises of organization's culture, business scope, top management's support, organizational readiness, prior ICT knowledge, owner innovativeness, information intensity, cost, and size [START_REF] Tornatzky | The process of technology innovation[END_REF].

Environmental Context: Factors facilitating or delaying areas of operation are covered under environmental context. [87, 8, and 65] have captured a number of significant factors including competitive pressure, socio-cultural issues, readiness of business partners, government support and encouragement, and infrastructures for technology support.

Based on the academic journal guide 2015, a literature review was directed to identify the empirical publications conducted on SMEs innovation adoption from high-ranking journals. Thirty-five journals has published empirical studies on SMEs innovation adoption, ranging from 4* to 1* rating, and a total of sixty-eight studies was identified (Table 1). These studies were conducted from 1995 to 2017, the highest number of studies has took place in 2005 (Figure 1). Based on TOE framework, a construct analysis has conducted to identify the most significant factors affecting SMEs adoption from the studies that has been identified in Table 1. From the technological factors, six constructs has been identified including relative advantage, compatibility, complexity, trialability, observability, and security. From the organizational factors, seven constructs has been identified including top management support, organizational readiness, prior ICT/IS knowledge, owner/ entrepreneurial innovativeness, information intensity, cost, and size. From the environmental factors, five constructs has been identified including external/competitive pressure, consumer pressure, industry sector, market scope, and external ICT support (Table 2). [START_REF] Poon | An exploratory study of small business Internet commerce issues[END_REF]; [START_REF] Ramdani | SMEs' adoption of enterprise applications: A technology-organisation-environment model[END_REF]; [START_REF] Tan | Internet-based ICT adoption: evidence from Malaysian SMEs[END_REF]; [START_REF] Teo | A contingency model of Internet adoption in Singapore[END_REF]; [START_REF] Van Huy | An empirical study of determinants of e-commerce adoption in SMEs in Vietnam: An economy in transition[END_REF]; [START_REF] Zhu | Innovation diffusion in global contexts: determinants of post-adoption digital transformation of European companies[END_REF] C B DV: BI [START_REF] Maduku | Understanding mobile marketing adoption intention by South African SMEs: A multi-perspective framework[END_REF] DV:USE [START_REF] Kendall | Receptivity of Singapore's SMEs to electronic commerce adoption[END_REF]; [START_REF] Grandon | Electronic commerce adoption: an empirical study of small and medium US businesses[END_REF] DV:USE [START_REF] Al-Qirim | A Research Trilogy into E-Commerce Adoption in Small Businesses in New Zealand[END_REF]; [START_REF] Alshamaila | Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework[END_REF]; [START_REF] Oliveira | Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors[END_REF]; [START_REF] Ramdani | SMEs' adoption of enterprise applications: A technology-organisation-environment model[END_REF]; [START_REF] Riemenschneider | Understanding IT adoption decisions in small business: integrating current theories[END_REF]; [START_REF] Tan | Internet-based ICT adoption: evidence from Malaysian SMEs[END_REF];[76] C X DV:USE [8] DV:USE [START_REF] Alshamaila | Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework[END_REF]; [START_REF] Kendall | Receptivity of Singapore's SMEs to electronic commerce adoption[END_REF]; [START_REF] Ramdani | SMEs' adoption of enterprise applications: A technology-organisation-environment model[END_REF]; [START_REF] Ramdani | Knowledge management and enterprise systems adoption by SMEs: Predicting SMEs' adoption of enterprise systems[END_REF]; [START_REF] Tan | Internet-based ICT adoption: evidence from Malaysian SMEs[END_REF]; [START_REF] Wymer | Factors Influencing e-commerce Adoption and Use by Small and Medium Businesses[END_REF] TR DV:USE [START_REF] Al-Qirim | A Research Trilogy into E-Commerce Adoption in Small Businesses in New Zealand[END_REF]; [START_REF] Kendall | Receptivity of Singapore's SMEs to electronic commerce adoption[END_REF]; [START_REF] Ramdani | Knowledge management and enterprise systems adoption by SMEs: Predicting SMEs' adoption of enterprise systems[END_REF] DV:USE [START_REF] Ramdani | SMEs' adoption of enterprise applications: A technology-organisation-environment model[END_REF]; [ [START_REF] Van Huy | An empirical study of determinants of e-commerce adoption in SMEs in Vietnam: An economy in transition[END_REF]; [START_REF] Wymer | Factors Influencing e-commerce Adoption and Use by Small and Medium Businesses[END_REF]; [START_REF] Zhu | Post-adoption variations in usage and value of ebusiness by organizations: cross-country evidence from the retail industry[END_REF]; [START_REF] Zhu | Innovation diffusion in global contexts: determinants of post-adoption digital transformation of European companies[END_REF]; [START_REF] Zhu | The process of innovation assimilation by firms in different countries: a technology diffusion perspective on e-business[END_REF]; [START_REF] Zhu | Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors[END_REF] EP DV: BI [START_REF] Maduku | Understanding mobile marketing adoption intention by South African SMEs: A multi-perspective framework[END_REF] DV:USE [START_REF] Fillis | A qualitative investigation of smaller firm e-business development[END_REF]; [START_REF] Levenburg | Does Size Matter? Small Firms' Use of E-Business Tools in the Supply Chain[END_REF]; [START_REF] Poon | Business environment and internet commerce benefit-a small business perspective[END_REF]; [START_REF] Wymer | Factors Influencing e-commerce Adoption and Use by Small and Medium Businesses[END_REF]; [START_REF] Zhu | Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors[END_REF]; [START_REF] Scupola | SMEs' e-commerce adoption: Perspectives from Denmark and Australia[END_REF]; [START_REF] Laforet | Innovative characteristics of small manufacturing firms[END_REF]; [START_REF] Ghobakhloo | Adoption of ecommerce applications in SMEs[END_REF] CP DV:USE [START_REF] Ramdani | Knowledge management and enterprise systems adoption by SMEs: Predicting SMEs' adoption of enterprise systems[END_REF] DV:USE [START_REF] Alshamaila | Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework[END_REF]; [START_REF] Chan | An empirical investigation of factors affecting e-collaboration diffusion in SMEs[END_REF]; [START_REF] Fillis | A qualitative investigation of smaller firm e-business development[END_REF]; [START_REF] Hong | Migrating to internet-based e-commerce: factors affecting e-commerce adoption and migration at the firm level[END_REF]; [START_REF] Poon | Business environment and internet commerce benefit-a small business perspective[END_REF]; [START_REF] Poon | An exploratory study of small business Internet commerce issues[END_REF]; [START_REF] Ramdani | SMEs' adoption of enterprise applications: A technology-organisation-environment model[END_REF]; [START_REF] Tan | Internet-based ICT adoption among SMEs: demographic versus benefits, barriers, and adoption intention[END_REF] IS DV:USE [START_REF] Buonanno | Factors affecting ERP system adoption: a comparative analysis between SMEs and large companies[END_REF]; [START_REF] Zhu | The process of innovation assimilation by firms in different countries: a technology diffusion perspective on e-business[END_REF] DV:USE [START_REF] Alshamaila | Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework[END_REF]; [START_REF] Jeon | Determining factors for the adoption of e-business: the case of SMEs in Korea[END_REF]; [START_REF] Kula | An exploratory study of Internet adoption by SMEs in an emerging market economy[END_REF]; [START_REF] Ramdani | SMEs' adoption of enterprise applications: A technology-organisation-environment model[END_REF]; [START_REF] Ramdani | Knowledge management and enterprise systems adoption by SMEs: Predicting SMEs' adoption of enterprise systems[END_REF]; [START_REF] Zhu | Post-adoption variations in usage and value of ebusiness by organizations: cross-country evidence from the retail industry[END_REF]

Summary and conclusion

The current study makes a significant contribution for academics by reviewing the literature of the empirical studies on SMEs innovation adoption from high-ranking journals. A total of thirty-five journals have presented empirical research papers on SMEs innovation adoption with sixty-eight different studies. The identified studies has been conducted from 1995 to 2017. Based on the TOE framework, a review of the constructs has directed to identify the most significant factors affecting SMEs innovation adoption from the selected journals. The study found that the most significant factors found to be relative advantage and compatibility from the technological context, top management support and size from the organizational context, and external pressure from the environmental context. This analysis intended to guide future researchers to improve the predictive power of their examined models.

  Figure 1. Empirical studies conducted according to journal rating and year

  [START_REF] Al-Qirim | An Empirical Investigation of an e-commerce Adoption-Capability Model in Small Businesses in New Zealand[END_REF];[START_REF] Ramdani | SMEs' adoption of enterprise applications: A technology-organisation-environment model[END_REF];[START_REF] Ramdani | Knowledge management and enterprise systems adoption by SMEs: Predicting SMEs' adoption of enterprise systems[END_REF] DV:USE[START_REF] Alshamaila | Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework[END_REF];[START_REF] Ghobakhloo | Adoption of ecommerce applications in SMEs[END_REF];[START_REF] Scupola | SMEs' e-commerce adoption: Perspectives from Denmark and Australia[END_REF];[82] ES IV: Independent variable, DV: Dependent variable, BI: Behavioural Intention, RA: Relative advantage, CB: Compatibility, CX: Complexity, TR: Trialability, OB: observability, SC: Security, TMS: Top management support, OR: Organizational readiness, PK: Prior ICT/IS knowledge , OI: Owner Innovativeness, II: Information Intensity, CO: Cost, SI: Size, EP: External Pressure, CP: Consumer pressure, IS: Industry sector, MS: Market Scope, ES: External ICT Support.

Table 1 . Empirical studies on SMEs innovation adoption from select journals

 1

	ISSN	Journal name	AJG 2015	ABS 2010	Articles
			Rating	Rating
	0276-7783	MIS quarterly	4	4	[32]
	1047-7047	Information systems research	4	4	[73];[84]
	0025-1909	Management science	4	4	[86]
	0883-9026	Journal of Business Venturing	4	4	[34];[63]
	0022-2437	Journal of marketing research	4	4	[24]
	0047-2506	Journal of International Busi-	4	4	[27]
		ness Studies
	0143-2095	Strategic Management Jour-	4	4	[71]
		nal
	1042-2587	Entrepreneurship Theory and	4	4	[48]
		Practice
	0090-4848	Human resource management	4	4	[30]
	0378-7206	Information & management	3	3	[12];[16]; [28];
					[31];[36] [46];
					[49]; [54]; [61]
	0925-5273	International Journal of Pro-	3	3	[14]
		duction Economics
	0921-898X	Small Business Economics	3	3	[19]
	0963-8687	Journal of Strategic Infor-	3	3	[35]
		mation System
	0309-0566	European Journal of Market-	3	3	[38];[64]
		ing
	0960-085X	European Journal of Infor-	3	3	[53]; [85];[87]
		mation Systems
	0305-0483	Omega: The International	3	3	[56];[74]
		Journal of Management Sci-
		ence
	1086-4415	International Journal of Elec-	3	3	[70]
		tronic Commerce
	0742-1222	Journal of management infor-	4	3	[72]
		mation systems
	0266-2426	International Small Business	3	3	[45]
		Journal
	0166-4972	Technovation	3	3	[44];[60];[83]
	0047-2778	Journal of Small Business	3	3	[10];[78];[81]
		Management

Table 2 . Construct analysis the most significant factors affecting SMEs adoption

 2

	IV	Significant	Insignificant
	Technological factors
		DV: BI [43];[61]	DV:USE [7];[8]
		DV:USE

[9];[12];[25];[26];[28];[32];[33];[35];[36];[46];[4

	R
	A
	7];[49];[52];[53];[54];[55];[56];[65]; [68];[70];[76]; [58]
	DV:USE

[4];[7];[8];[9];[12];[25];[26];[28];[35];[47];[49];[ 52]

[9];[12];[14];[47];[49];[54];[55];[56];[58];[59];[6

	O	68]
	B
	SC	DV:USE [40];[19];[21];[85];[68]
	Organizational factors
	T	DV: BI [43]
	M S	DV:USE5];[70];[84]
		DV: BI [14]	DV: BI [47]
		DV:

USE[28];[32];[36];[46];[47];[49];[52];[58];[59];[82];[

	O
	R
		86]
	PK	DV:USE [7];[19];[26];[33];[40];[72];[73];[74];[76];[82]	DV:USE [26];[58];[59]
		DV:

USE[7];[21];[25];[26];[33];[39];[72];[73];[74];[76];[8

	OI
	2]
	DV: BI [26];[72];[74]	DV: BI [7];[70]
	DV:USE [26];[37];[41];[54]

II DV:USE[7];[8];[35];[26

	C	DV: BI [43]
	O	DV:USE [4];[8];[21];[25];[40];[82];[84];[85]	]; [33]
		DV:USE	DV:USE [26];[33]

[7];[9];[13];[19];[31];[49];[56];[58];[59];[69];[72

	SI
	];[73];[74];[76];[84];[87]
	Environmental factors
	DV: BI [43]
	DV:USE[7];[9];[33];[37
	];[47];[49];[59]; [70]

DV:USE[14];[19];[26];[28];[32];[36];[56];[46];[52];[58];