Internet adoption and usage: evidence from Italian

Int. J. Entrepreneurship and Small Business, Vol. 30, No. 2, 2017

Internet adoption and usage: evidence from Italian micro enterprises Federica Pascucci* and Silvio Cardinali Department of Management, Università Politecnica delle Marche, Italy Email: [email protected] Email: [email protected] *Corresponding author

Chiara Gigliarano Department of Economics, Università degli Studi dell’Insubria, Italy Email: [email protected]

Gian Luca Gregori Department of Management, Università Politecnica delle Marche, Italy Email: [email protected] Abstract: This study aims to fill a gap in the literature of internet adoption and usage within a micro enterprises (MEs) context. The aims of the research are twofold: a) to investigate the factors that influence the adoption of internet in MEs in developed countries; b) to characterise the MEs in term of internet usage and tools adopted and benchmark different typologies of them. After a thorough analysis of the literature, a research model is created. It consists of two parts. In the first part, four hypotheses are developed in order to investigate the different factors relevant to internet adoption (company size, geographical location, type of industry, and level of internationalisation). In the second part of the research, through a cluster analysis, we analyse the main differences related to internet usage. The statistical analysis was carried out on a sample of 600 Italian MEs. The research shows that the use of the internet is still not widespread. As shown from the regression analysis, the decision to use this technology is influenced by the size of the company, the sector it operates in, and the level of internationalisation, while location is not a significant factor. Cluster analysis shows three different groups of firms related to internet usage. Keywords: micro-enterprises; digital marketing; internationalisation; internet adoption; internet usage; company size; geographical location; type of industry; cluster. Reference to this paper should be made as follows: Pascucci, F., Cardinali, S., Gigliarano, C. and Gregori, G.L. (2017) ‘Internet adoption and usage: evidence from Italian micro enterprises’, Int. J. Entrepreneurship and Small Business, Vol. 30, No. 2, pp.259–280.

Copyright © 2017 Inderscience Enterprises Ltd.

259

260

F. Pascucci et al. Biographical notes: Federica Pascucci received her PhD in Economy and Management of Firms in 2002. Since 2006, she is an Assistant Professor of Internet and Marketing at Economics Faculty ‘G. Fuà’, Università Politecnica delle Marche, Italy. She conducts research on digital marketing and international marketing, with particular reference to the small and medium sized firms and she is author of various articles and a monograph on these subjects. Silvio Cardinali is an Associate Professor at the Economics Faculty ‘G. Fuà’, Università Politecnica delle Marche. He teaches communications and sales management. He is the author of various articles and monographs on sales management and geomarketing. He is a Lecturer at LUISS Business School and ISTAO. Chiara Gigliarano is an Assistant Professor of Statistics at the Economics Department, University of Insubria, Varese. She is also a Teaching Expert in Statistics at Bocconi University. She received her PhD in Statistics at Bocconi University, Milan in 2007. She has published in international journals such as Lifetime Data Analysis, Computational Statistics and Data Analysis, Journal of Economic Inequality, Metron, Social Indicators Research and the International Journal of Microsimulation. Her research interests are in the fields of income distribution, Gini index, polarisation and deprivation measurement as well as survival analysis. Gian Luca Gregori is a Full Professor at Economics Faculty ‘G. Fuà’ and Vice Rector at Università Politecnica delle Marche. He teaches marketing and business marketing. He is the Vice President at ISTAO Business School. This paper is a revised and expanded version of a paper entitled ‘Fattori influenti sul ricorso ad internet nei processi gestionali delle micro-imprese’ presented at XXV Convegno Annuale di Sinergie, Ancona, Italy, 24–25 October 2013.

1

Introduction

In light of the economic relevance of micro enterprises (MEs) in European and non-European countries (Dana, 2008; European Commission, 2014; Lieberman-Yaconi et al., 2010), it appears quite surprising that very few studies have been conducted on the internet usage by these firms. This paper tries to fill a significant gap in the literature of internet adoption and usage within a MEs context. Indeed, microenterprises is a relatively novel field of study (Thapa, 2015) and it was indicated as a research priority by a panel of experts (Dana and Wright, 2009); currently academic research specifically focused on MEs is rare and fragmented (Clark and Douglas, 2011; Reid, 1995; Kelliher and Reinl, 2009). This is particularly true as regards the internet domain. Little has been published on the technological behaviour of this particular type of enterprise (Bordonaba-Juste et al., 2012; Burke, 2013; Clark and Douglas, 2011; Davis and Vladica, 2006; Fillis et al., 2004; Jones et al., 2014; Setiawan et al., 2015). The smallest enterprises are even explicitly excluded from some research samples (Bayo-Moriones and Lera-Lopez, 2007; Wade et al., 2004). Studies on MEs took

Internet adoption and usage: evidence from Italian micro enterprises

261

in consideration high tech sectors, home-based business (Clark and Douglas, 2011); or the new business in emerging markets (Thapa, 2015). The objective of this work is to fill this gap by analysing the present state of internet adoption/usage by MEs, operating in traditional sectors and in a developed country. Empirical studies show a relevant and positive relationship between internet usage and the economic performance of SMEs, measured in terms of increased revenues and reduced costs (Davis and Harveston, 2000; Drennan and McColl-Kennedy, 2003; Gërguri-Rashiti et al., 2015; Johnston et al., 2007). Several researches also confirm that firms that are active online grow more rapidly and have a higher degree of internationalisation than firms that are not (The Boston Consulting Group, 2012, 2013). Alderete (2014) found a positive and significant influence of the ICT development on entrepreneurship; moreover internet can facilitate the internationalisation of entrepreneurship, as indicated by the term ‘internetisation’ (Etemad et al., 2010). Despite these favourable conditions, MEs in developed countries have not yet taken advantage of the opportunities offered by the digital world; recent studies revealed that internet usage by small businesses in European countries also remains rather low (BCG Perspectives, 2013; Chatzoglou and Chatzoudes, 2016). The aims of this research are twofold: 1

to investigate the factors that influence the adoption of internet in MEs

2

clustering the MEs in terms of internet usage and benchmarking the different clusters of firms.

The literature on innovations adoption by SMEs (ICT and the internet, in particular) is the underlying basis upon which the research framework and hypotheses are built. These hypotheses undergo empirical testing on a sample of 600 Italian businesses; Italy is a suitable context in order to analyse this type of firms, because MEs accounts for the 95% of the total number of Italian enterprises (Istat, 2015). The remainder of this article is structured as follows. A brief review of the literature pertaining to the relationship between the internet and MEs is presented, followed by the description of the research model, hypotheses, and methodology. In the final sections, the findings and the main implications are discussed, along with limitations of the study and future research paths.

2

Entrepreneurship in Italy: some introductive observations

Italy is characterised by a system of diffused entrepreneurship, in which micro and small size is dominant, often organised with the form of industrial districts. Three characteristics define Italian industrial districts model that are: a

the flexible specialisation

b

a shared culture and common roots along with supportive institutional environment

c

a network-based organisational structure, in which vertical and horizontal cooperation takes place, often enhanced by the presence of ‘thick’ institutions.

They tend to specialise in traditional sectors (for example, textile, furniture, mechanics) characterised by low entry barriers and low technological opportunities; so, innovation is

262

F. Pascucci et al.

mainly driven by incremental rather than radical change. In coherence with this model, Toninelli and Vasta (2014) identified two distinguishing characteristics of entrepreneurship in Italy, that are the openness to foreign markets and the low aptitude to innovate from the techno-scientific point of view. Another peculiarity of Italian entrepreneurship is the large presence of family businesses. In Italy there are estimated to be around 784,000 family businesses – more than 85% of the total number of business – constituting around 70% of employment. In terms of the impact of family businesses, the Italian context is in line with that of the main European economies, such as France (80%), Germany (90%), Spain (83%) and the UK (80%); the factor that sets Italy apart from these countries is the lesser recourse of family businesses to external managers: 66% of Italian family businesses are fully managed by family members, while this applies to only 26% of French family businesses and just 10% in the UK (http://www.aidaf.it). Family firms and industrial districts represent the pillars of the Italian manufacturing industry. More recently the autonomous category of ‘medium-sized firms’ is becoming more important in the Italian industrial system. Italian medium-sized family businesses have a clear historical identity. They developed in the 1950s and 1960s during the Italian economic boom, and consolidated in the 1970s. Today there are more than 4,000 medium-sized family businesses, mainly concentrated in the northeast and centre of Italy (Ciambotti et al., 2012). Because of their liveliness, good economic performances, high propensity to internationalisation, they are considered the standard-bearer of Made in Italy in the global markets (Varaldo et al., 2009).

3

Internet and MEs: a literature review

3.1 MEs and internet adoption The relationship between company size and internet adoption is an issue of vigorous debate (Simmons et al., 2008) that can be explained through two different perspectives. First, size is a proxy for the availability of resources to invest. According to this view, smaller business size represents an obstacle to the adoption of technology, because it implies a lack of financial, managerial, and knowledge resources that characterises smaller enterprises (Brown and Kaewkitipong, 2009; Tan et al., 2010). Second, size is a proxy for information complexity within the organisational structure of the firm. According to this view, smaller-sized businesses do not perceive the need to adopt the internet as a tool, because their information needs are less complex than those of larger firms. As the organisation grows, the degree of complexity to be managed also grows, and there is increased incentive to invest in internet technology (Burke, 2005). While the research on ICT adoption by SMEs is well developed, understanding of MEs’ behaviour is limited (Jones et al., 2014). From the analysis of international literature a significant knowledge gap on internet adoption and usage by small businesses, especially by microenterprises, emerges. The majority of SMEs ICT research fails to distinguish MEs from larger SMEs (Burke, 2013). They face specific challenges in adopting ICT – such as little training in ICT usage and lack of awareness of the benefits – which are more pronounced for smaller firms (Wolcott et al., 2008).


263

Some scholars have highlighted the existence of a digital divide, both within the category of SMEs as well as between them and large enterprises (Arbore and Ordanini, 2006). According to Levenburg (2005), there are not only significant differences among micro-, small-, and medium-sized enterprises regarding technology usage in the sense that micro-enterprises are lagging behind the others and their usage is very basic, but there is also variance in the entity of the consequent benefits. Thus, it could be too limiting to investigate the relationship between internet adoption/usage and SMEs without taking into consideration the size variance of the enterprises, with the consequence being inconsistency and contradiction in the research findings (Bengtsson et al., 2007; Bordonaba-Juste et al., 2012; Burke, 2005; Levenburg, 2005; Parker and Castleman, 2007). Regarding the factors (both internal and external to the company) that either hinder or facilitate the adoption of the internet as a management tool, the literature review reveals the following. According to Hairuddin et al. (2012), the main obstacles faced by micro-enterprises are the lack of knowledge and capability as well as scarcity of financial resources. The characteristics inherent to the sector are also considered among the influencing factors, particularly intense competition (Dholakia and Kshetri, 2004; Hollestein, 2004; Pontikakis et al., 2006), type of business activity (Cheung and Huang, 2002), pressure from international competition (Hollestein, 2004), and pressure from clients and suppliers to adopt new technologies. Stansfield and Grant (2003) found that business type is a stronger determinant than business size regarding the utilisation of internet-related technologies. Arbore and Ordanini (2006) found a relevant relationship between the size of the city in which the firm is located and the adoption of a broadband internet connection. This is especially true for smaller-sized businesses located in small towns or rural areas where fewer resources are available (e.g., fewer IT specialised services or providers), making it more difficult for those businesses to effectively use innovative technologies.

3.2 MEs and internet usage The use of the internet is changing the conventional way of doing business among all categories of firms, including very small ones. The internet may be used by very small firms to accomplish a number of different activities within the firm’s value chain, including gathering information, communicating with customers, purchasing goods and services, and selling products. In the literature, the term ‘e-business’ is generally used to encompass these multiple applications of the internet in an organisation. Internet marketing (or digital marketing, online marketing, or interactive marketing) is a specific dimension of e-business, and it refers to the use of digital interactive technologies to conduct marketing activities (Varadarajan and Yadav, 2009). E-commerce is another different concept that refers to the development of online transactions. The literature on e-business, and in particular on digital marketing in micro and small firms, is very scant (Caniëls et al., 2015). Only few studies focus on this specific group of firms, and the majority of these are qualitative, based on case study methodology (Barnes et al., 2012; Durkin et al., 2013; Gilmore et al., 2007). Other studies focus on businesses with more than 50 employees, thus excluding micro and/or small firms (Durkin et al., 2013; Kim et al., 2011). Still, other analyses do not consider the differences in firm size

264

F. Pascucci et al.

(Gilmore et al., 2007; Hanafizadeh et al., 2012; Santarelli and D’Altri, 2003; Solaymani et al., 2012). Voges and Pulakanam (2011) found that business size only affects the number of internet uses within the firm; larger companies (21–200 full-time employees) show a higher number of uses than smaller ones (1–20 full-time employees). The internationalisation also influences the number of internet uses. The advent of used generated content has created new ways to communicate with customers and to support corporate brand strategy. Within the SME context, in which personal contact networks are crucial to do business, studies on social media adoption and utilisation are limited (Abed et al., 2015; Durkin et al., 2013; Nobre and Silva, 2014). SMEs differ not only in size, but also in other characteristics. Thus, it must be recognised that new tools may not be suitable for all, such as in the case of blogs (Chua et al., 2009). Nakara et al. (2012) shown that some SMEs and entrepreneurs still question the social media credibility and sustainability. E-commerce can provide small firms the opportunity to enlarge their markets in an efficient and rapid way. Larger businesses have mostly benefited from e-commerce adoption because of a series of barriers faced by smaller ones, such as the lack of technical knowledge, financial resources, and time (MacGregor and Vrazalic, 2005). Van Beveren and Thomson (2002) found that company size is also relevant since smaller firms are less likely to adopt e-commerce. Bengtsson et al. (2007) found that organisational-level factors may not be able to adequately capture the adoption processes of small firms (< 19 employees). Individual-level models focused on individual decision makers may be better suited for studying the adoption of advanced internet-based marketing operations. Many researchers agree that individual owner characteristics have a significant influence on small business decision-making, and so they cannot be ignored (Fillis and Wagner, 2005; Peltier et al., 2012; Simmons et al., 2008; Weltevreden and Boschma, 2008). In particular, the age of the firm owner is one of the characteristics most cited in the literature. These fragmented and incomplete research results present an evident knowledge gap regarding how MEs are using internet-related technologies, especially for marketing activities.

4

Research model and hypothesis

The aim of this study is to understand if and how much MEs use the internet in their marketing activities along with factors that most greatly influence its adoption/usage. The research consists of the two following parts: •

Part 1: The structural factors that explain internet adoption in MEs firms.

•

Part 2: The way internet is used in marketing processes in terms of purposes and online activities.

Part 1 in the research model strives to describe internet adoption in the management of micro-enterprises as a function of the following four variables (see Figure 1).

Internet adoption and usage: evidence from Italian micro enterprises Figure 1

265

Research model and hypotheses (see online version for colours) Firm size

Geographic location of firm

Economic sector

H1 H2 H3

Internet adoption in management processes

H4 Geographic size of sales market

1

Firm size, that is the availability of internal resources and competences, which can be utilised to adopt technology effectively. Studies focused on the relationship between firm size and the internet adoption (as well as ICT) yield contrasting results. Some show the existence of a positive relationship (Arbore and Ordanini, 2006; Bordonaba-Juste et al., 2012; Burke, 2005; Chatzoglou and Chatzoudes, 2016; Dandridge and Levenburg, 2000; Dholakia and Kshetri, 2004; Jones et al., 2011; Levenburg, 2005). Others do not reveal any relevant relationship (Pontikakis et al., 2005; Tan et al., 2010). The non-homogeneous nature of prior findings points to the need for further research into the role played by the firm size. This leads to the first research hypothesis: H1 Internet adoption is positively influenced by firm size.

2

Geographic location of the firm, that is the availability of external resources, which can facilitate or hinder the internet adoption. Considering the limited internal resources of the small enterprises, the quantitative and qualitative offer of external services can represent a determining factor, both technically and strategically, in the decision to adopt the internet as a management tool. Depending on where the business is located, the services offered and the available infrastructure may vary considerably, in reference to large cities or rural areas, coastal areas or inland areas, and among different provinces. This leads to the second research hypothesis: H2 Internet adoption is positively influenced by the demographics of the area in which it is located.

3

Economic sector, that is the type of business activity undertaken by the organisation. Results of prior studies on the influence of the economic sector on a firm’s propensity to adopt the internet are not univocal. Some suggest that features pertaining to the sector (Burke, 2013; Love et al., 2005) have an influence on the internet adoption (and ICT in general). Others conclude that there is no such influence (Bordonaba-Juste et al., 2012; Pontikakis et al., 2005). Bengtsson et al. (2007) found that market pressure only exerts marginal influence on internet usage

266

F. Pascucci et al. by SMEs, regardless of their size. Thus, additional research on sector influence is needed. This leads to the third research hypothesis: H3 Internet adoption is influenced by the economic sector in which the firm operates.

4

Geographic size of sales market, that is the scope of a firm’s market, which can be very small (only provincial or regional levels, at best) or much larger (even to the international level). Several studies shown the positive relationship between firm’s geographical scope/internationalisation and internet adoption, because web-based technologies enhance information collection and sharing, reduce research costs, favour inter-firm collaboration (Chatzoglou and Chatzoudes, 2016; Putra and Hasibuan, 2015). So, the presence on the international market can be considered as an antecedent to the adoption of the internet (Bayo-Moriones and Lera-Lopez, 2007), leading to testing of the fourth hypothesis: H4 Internet adoption is influenced by the firm’s local, domestic, and international market size.

The part 2 of the research is restricted only to the firms that actually adopt the internet for their business; through a cluster analysis, we analyse the main differences related to internet usage, in terms of purposes and implemented online activities. Concerning internet usage, in the literature there are not consolidated criteria for measuring it (Kula and Tatoglu, 2003). Therefore, this analysis adapts the work of Dutta and Evrard (1999), which distinguishes the five main types of internet usage – communication, researching information, marketing, conducting business with suppliers, and conducting business with customers. In addition an exploration of tools adopted is carried on.

5

Methodology and sample

The research model is empirically tested on a sample of 600 firms settled in the Marche region (region with the highest concentration of MEs in Italy) in 2013 by means of a structured questionnaire administered through a telephone survey. Italy is the country with the highest number of SMEs (99.9% of total firms),1 and the majority of these are MEs (95%; Istat, 2015). Among these, artisan businesses carry significant weight in terms of numbers (28.1% of Italian businesses), employment figures (18.3% of the total), and national added value (12.8% of the total). The sample was collected in the Italian (Marche region) artisan enterprises, as a stratified sample (based on the sector and location) of regional enterprises in the ‘Asia’ archive produced by Istat. In particular, looking at the distribution of the firms in the sample by size (by number of employees), 35% of the enterprises are sole-proprietor, 38% have 5 or fewer employees end the rest have more than 5 employees. To answer the first research question and to test the impact of the factors presented in Figure 1 regarding internet adoption by firms, a logistic regression model is developed in which the dependent variable is represented by the probability of using the internet (y = 1) compared to the probability of not using it (y = 0). Internet adoption is seen as a decision taken by the firm to use the internet in its business and is determined by a binary measure. This conceptualisation and measurement are widely used in a large number of


267

scientific publications (Al-Qirim, 2007; Hashim et al., 2010; Oliveira and Martins, 2008; Pontikakis et al., 2006; Premkumar and Roberts, 1999; Tan et al., 2009). They are based on the two most used and popular frameworks about innovation technology adoption at the firm level: the diffusion of technology innovation model (Rogers, 1995) and the technology, organisation, and environment model (Tornatzky and Fleischer, 1990). The logistic regression model is applied in cases in which the dependent y variable is dichotomous, as in the scenario under analysis. The logit model is defined as: ⎛ p ⎞ logit ( p ) = log ⎜ ⎟ = β0 + ⎝ 1− p ⎠

∑

K i =1

β i xi ,

where logit(p) is the logit function, p is the probability that the event y = 1 will take place, and x1, x2, …, xK are the explanatory variables. This model assumes that it is the logit transformation of the probability of using the internet that has a linear connection to the predictor variables. The explanatory variables are the number of employees (as a firm size proxy), the size and proximity to the coast of the municipality in which the firm is located (as a proxy of geographic location), the ATECO code referring to the firm’s business activity (as a proxy of the economic sector) and the percentage of turnover at each of the regional, national, and international levels (as a proxy of the geographic size of the sales market). Each model is tested for multicollinearity among the independent variables using the variance inflation factor (VIF). If the VIF index values are greater than 10, then the independent variable can be considered a linear combination of the others, whereas in the case of a model with a single regressor, the VIF index is 1. All of the regressors for the six models present indicator values that are well below the critical threshold (the maximum value is equal to 2.43 for the size of the municipality, as shown in Table 2). This reveals an absence of multicollinearity in the models proposed. Concerning part 2 of this research, the following five practices are conceived as purposes of internet use: find information (INFO), purchase goods or services (PURCHASE), manage customer relationship (CUS_REL), advertise (ADV), and sell goods or services (E-COMMERCE); all of these purposes are measured in a binary mode (Dutta and Evrard, 1999). Six additional variables describing the types of activities implemented online are also measured in a binary mode, following the frameworks proposed in other studies (Stansfield and Grant, 2003); they are the following corporate website (WEB SITE), e-mail marketing (E-MAIL MKGT), blog/forum/social network (WEB 2.0), online advertisement (banner, pop up) (ONLINE ADV), paid links in search engines (PAID LINKS), and organic positioning in search engines (ORG_POS). This second part of the research is handled through the means of a cluster analysis, with the aim of detecting similarities or differences among the MEs in the way they use the internet. Cluster analysis maximises both the similarity of firms within each group (internal cohesion) and the dissimilarity between firms of other clusters (external isolation). To perform the hierarchical clustering, a measure of proximity among objects must be defined. Since the variables referring to internet usage are binary variables with only two outcomes (0/1), we considered as a similarity measure the simple-matching coefficient, corresponding to the ratio of the total number of variables on which the two individuals match (a10 + a01) over the total number of variables (d):

268

F. Pascucci et al. d (i, j ) =

a10 + a01 d

Thus, a proximity matrix is built. The agglomerative hierarchical clustering procedure transforms such proximity matrix into a sequence of nested partitions that consists of a series of consecutive and irrevocable fusions of clusters. Initially each item represents a cluster of its own, and at each step the most similar items/groups are joined together into a single cluster. The procedure continues until a unique cluster containing all of the observations is obtained. Once a hierarchy of the enterprises is obtained, the best partition of groupings is identified through the dendrogram inspection and by means of a K-mean clustering. Ward’s dendrogram method suggests a three-cluster partition of the firms.

6

Main findings

6.1 Internet adoption and its determinants The research findings show that less than a third (31.17%) of MEs adopted the internet for their business activity, and the remaining two-thirds (68.83%) stated that they did not adopt it. The average number of workers in MEs that did not adopt the internet is 3.4, whereas the average is 7.4 in those enterprises that did navigate on the internet. Therefore, it appears that size significantly influences internet adoption by MEs in the Marche region. As shown in Table 1, the principal sectors in which there is the heaviest internet adoption are the mechanical and the woodworking sectors, while the family services sector is less interested in the internet adoption. Table 1

Propensity (%) for internet adoption by subgroups

Economic sector*

Size of sales market

Textile

31.22

Only within the province

16.1

Footwear

32.94

Only within the region

27.2

Wood

58.82

Only within Italy

55.5

Mechanical

57.14

Also in Europe

81.5

Other manufacturing

35.29

Also outside Europe

60.0

Family services

3.49

Other services

10.31

Coastal municipality

Number of inhabitants

No

32.39

8,600

30.03

Notes: * ‘Other manufacturing’ includes all activities that are not considered part of the other sectors, among which are agro-industrial and chemical activities; building and construction activities are instead excluded. ‘Other services’ includes services to businesses and to communities and services that can also involve commercial activity.


269

No marked differences seem to exist in the propensity for internet adoption among coastal and non-coastal municipalities, as shown in Table 1. Table 1 also shows that the size of the municipality in which the business is located did not seem to affect the number of enterprises adopting the internet. In particular, the figures are about the same, regardless of whether the firm is located in a municipality with a population below or above the regional average for the Marche (approximately 8,600 inhabitants). Table 1 also illustrates how the size of enterprises’ sales markets heavily influences the internet adoption. Only 16.1% of businesses that sell their products exclusively within the province use the internet, while the percentage rises considerably if the products are sold throughout the region (27.2%) and the nation (55.5%). Exports to Europe and abroad have an even greater effect on the internet adoption, which grows to 81.5% in businesses that export their products to other European countries and reach 60% in those that also trade outside of Europe. To establish whether the evidence from Table 1 is statistically relevant, six different logistic regression models (see Table 2) are estimated. The first four models separately analyse the effects of each explanatory variable. The first model (M1) analyses the municipality (i.e., its size and proximity to the coast) where the artisan enterprise is located. The second model (M2) studies the impact of the number of workers. The third (M3) analyses the effects of the enterprise’ sales market size. The fourth (M4) looks at the differences by economic sector. The last two models (M5 and M6) focus on the joint effects of these covariates. Table 2

Estimates of the seven logistic regressions M1

Size of the municipality Coastal municipality Total workers Size of sales market (ref.: within the province) Outside Europe Within the EU In Italy Within the region Economic sector (ref.: textile)

M2

M3

–0.033 –0.172 0.156

2.060 3.136 1.874 0.669

M5

*** *** *** ***

1.520 2.739 1.540 0.556

0.618 * –0.940 ** 0.513 1.580 *** 1.511 *** –2.096 *** 599 598 600 0.5181 0 0 0.0018 0.102 0.148 2.03 1 1

M6

–0.236 –0.041 0.186 0.120 0.099 *** 0.098

***

Other manufacturing sectors Other services Footwear Woodworking Mechanical Family services Sample size (n) P-value(chi-square) Pseudo R-square VIF

M4

600 0 0.167 1

*** *** *** **

0.709 2.430 1.257 0.231

0.540 0.062 0.778 1.959 1.817 –0.905 597 0 0.186 1.57

597 0 0.276 1.53

270

F. Pascucci et al.

The univariate regression models reveal that: 1

neither the size of the municipality nor its proximity to the coast have a relevant impact on internet adoption

2

the probability for internet adoption increases when the number of workers employed in an enterprise rose

3

enterprises that sell their products outside of the province (in the region, in Italy, in Europe or abroad) adopt the internet significantly more than enterprises whose customers are predominantly local

4

enterprises in the woodworking and mechanical sectors adopt the internet significantly more than those in the textile sector; the family services sector showed the least use of all.

Model M5 studies the combined effects of the features of the territory where the enterprise is located (size of the municipality and its proximity to the coast) along with the size of the firm and its exports. The estimates obtained are analogous to those of models M1 through M3. Model M6 represents the final complete model, which takes into account the combined effects of all of the explanatory variables considered. Of note is how the impact of all the explanatory variables on the variable target (i.e., sign of the coefficients) remains nearly constant throughout the various models considered, thereby indicating the robustness of the estimates. One can conclude that, by keeping all regressors fixed, the probability of adopting the internet does not depend statistically on the size of the municipality in which an enterprise is located or on its proximity to the coast. This finding remains consistent in all of the models considered. Firm size again shows a clear impact on the propensity for the internet adoption as, ceteris paribus, the increased number of workers raises the probability that the enterprise would utilise the internet for business purposes. This confirms the first research hypothesis (H1). Differences in internet adoption are also due to the economic sector in which the enterprises operate, thus confirming the third research hypothesis (H3). Table 2 plainly shows how the economic sector (especially woodworking, mechanical, and footwear) significantly influences the probability of using the web, all other regressors remaining equal. Specifically, the odds (i.e., ratio between probability p of using the internet and the probability of not using it) in woodworking firms are equal to 3.6, the odds in mechanical firms are 7.2, and the odds in footwear firms are 2.3 times the odds for internet adoption by firms in the textile sector. The textile sector is chosen as the reference value because its internet usage is closest to the average figure. The fourth research hypothesis is also confirmed by empirical evidence. The analyses clearly show that the larger the sales market, the larger the probability of internet adoption. In contrast to model M5, once the economic sector is inserted in model M6 as a control variable, the level sales of goods and services within the region or abroad is no longer statistically relevant. In particular, in comparison to enterprises that only sell within their province, the odds of internet adoption among enterprises that sell in all of Italy are 3.6 times greater, and the odds among enterprises that export to European nations are 7.9 times greater.


271

In the M6 model, ‘Family services’ and ‘Other services’ lose relevance because they are heavily dependent on the level of internationalisation, as shown in Table 3. Selling within the region loses relevance because it is heavily dependent on the footwear sector (which becomes relevant in model M6). Internationalisation outside of Europe loses relevance because it is heavily dependent on footwear (which becomes relevant in model M6), woodworking, and mechanical sectors. It is therefore evident that dependence exists between the economic sector and the level of internationalisation, as well as between the firm’s business sector and its province of provenance. Table 3

Relationship between size of sales market and economic sector Mostly in the province

Mostly in the region

Mostly in Italy

Within Europe

Outside of Europe

Total

Other manufacturing

39.71

14.71

33.82

8.82

2.94

100

8.33

10.99

16.79

22.22

10

11.35

Other services

79.38

13.4

7.22

0

0

100

23.77

14.29

5.11

0

0

16.19

45.88

31.76

11.76

4.71

5.88

100

12.04

29.67

7.3

14.81

25

14.19

Woodworking and furniture

37.65

16.47

30.59

7.06

8.24

100

9.88

15.38

18.98

22.22

35

14.19

Mechanical

36.26

14.29

35.16

7.69

6.59

100

10.19

14.29

23.36

25.93

30

15.19

100

0

0

0

0

100

26.54

0

0

0

0

14.36

34.48

16.09

44.83

4.6

0

100

9.26

15.38

28.47

14.81

0

14.52

54.09

15.19

22.87

4.51

3.34

100

100

100

100

100

100

100

Sector

Footwear

Services to people Textile Total

To determine the order of importance of the explanatory variables considered in the analysis, it becomes necessary to compare the pseudo-R2 indices for each univariate logistic regression model (indicated in Table 2). As it is observed, the variables that identify the localisation of the artisan enterprises do not have a conjoint relative impact on the propensity for internet adoption (p-value of the chi-squared test is far greater than any level of acceptable relevance and pseudo-R2 equalled zero). The best explanatory variables for internet adoption are (in increasing order of importance) number of workers employed (pseudo-R2 equals 0.102), size of the firm’s sales market (pseudo-R2 equals 0.148), and economic sector in which it operates (pseudo-R2 equals 0.167).

272

F. Pascucci et al.

6.2 Purposes and activities with the internet Attention is now restricted only to the firms that actually adopt the internet for their business. The study analyses their main differences both in terms of purposes for web usage and activities related to the web. Table 4 clearly shows that almost all of the firms use the internet for e-mail service (97%); e-mail is a general-purpose instrument that can be used for a variety of activities. A great majority of the firms also use the internet to facilitate relationships with their customers (76%), information searching (68%) and e-procurement (64%). Less popular is web use for advertisement (42%) and online sales (8%). Looking at the activities (or instruments) related to the web, it can be noticed that several firms use the e-mail service but not with the explicit purpose of engaging in marketing (only 54% declare using e-mail for marketing). However, using e-mail for marketing remains the main activity on the web, together with managing a website (48%). Very few firms use pay-internet instruments, such as banners, links, or online advertisements, while slightly more popular is the use of social networks and blogs. Table 4

Frequency (%) of the firms by purpose and instruments in internet usage

Purpose of internet use For e-mail

97%

For info search

68%

For ordering

64%

For customer relationship

76%

For advertisement

42%

For online sales

8%

Online activities Email marketing

45%

Blog/social network

16%

Advertisement online (banner, pop-up)

9%

Buying link

6%

Search engine positioning

12%

Web site

48%

Once the optimal firms partition is identified through cluster analysis, it is interesting to study the main differences among the three groups and to assess, by means of several statistical tests, whether the three clusters were statistically distinct according to these variables. Table 5 summarises the most important descriptive factors of the groups, while Figure 2 provides a graphical representation.

Internet adoption and usage: evidence from Italian micro enterprises Table 5

273

Clusters description Cluster 1 medium-end internet users

Cluster 2 high-end internet users

Cluster 3 low-end internet users

Chi2 p-values

Cluster size (%)

47.3

9.6

43.1

Email (%)

97.73

100

96.59

100

92.86

60.23

0.00

95.45

71.43

50

0.00

Info search (%) Ordering (%)

0.75

Customer relationship (%)

86.36

100

75

0.05

Advertising (%)

63.64

78.57

22.73

0.00

Website (%)

81.82

92.86

45.45

0.00

Email for marketing (%)

95.45

92.86

22.73

0.00

Blog and social networks (%)

27.27

71.43

4.55

0.00

Online advertisement (%)

2.27

100

1.14

0.00

Links (%)

0

85.71

0

0.00

Positioning (%)

15.91

92.86

1.14

0.00

Online sales (%)

13.64

14.29

4.55

0.14

60

54.55

36.9

0.07

Holder's age: below 50 years old (%) Size of sales market Within province or within region (%)

0.67 29.55

50

39.77

In Italy (%)

47.73

35.71

40.91

In Europe or outside Europe (%)

22.73

14.29

19.32

Economic sector

0.00

Other manufacturing (%)

9.09

35.71

1.14

Footwear (%)

11.36

0

13.64

Woodworking and furniture (%)

56.82

21.43

19.32

Mechanical (%)

15.91

21.43

47.73

Textile (%)

6.82

7.14

18.18

Family services

0

0

0

Other services (%)

0

14.29

0

8.14

8.79

7.06

Number of employees

0.45

All of the variables have a significant impact in discriminating the three groups, with the exception of e-mail, online sales, size of sales market, and number of employees (see p-values of the chi-square test in Table 5). The second cluster seems to be characterised by a more advanced use of the web (with 9.6% of the sample). In comparison with the other two clusters, the use of web instruments and their purposes is much more popular.

274

F. Pascucci et al.

The third cluster is the least developed in terms of purposes and instruments for web usage. The firms in this group, most of which have older entrepreneurs and are mainly in the mechanical sector (B2B), use the internet mainly for general purposes (information search) and very rarely for advertising. The first cluster represents an intermediate scenario. In comparison to the second cluster, it uses mainly traditional web instruments (website and e-mail rather than social networks, blogs, or links), and it does not use the internet for search engine positioning and optimisation. Mainly woodworking and furniture firms characterise this cluster. Figure 2

7

Clusters comparison (see online version for colours)

Conclusions and implications

From a theoretical point of view, this study offers an original contribution to the debate surrounding the MEs’ adoption/usage of the internet. In the majority of management studies, this category of firms is included in the broader aggregate of SMEs. However, micro/small/medium firms do not present similar characteristics. The first finding regards the limited use of online tools by MEs. Only 31.7% of them declare that they utilise the internet in their management processes. In particular, digital marketing and e-commerce are still in their infancy for the majority of sampled MEs, and so there is a significant potential to be exploited. E-mail marketing and corporate websites are the two most implemented tools, but online advertising, social network communication, and search engine marketing activities are lagging behind with a considerable gap. The findings also confirm that micro-enterprises lag behind small enterprises regarding internet usage, particularly for e-mail marketing and corporate websites, in line with other authors (Burke, 2005; Jones et al., 2011). Internet adoption is not uniform in the different economic sectors. For example, it is more frequent in manufacturing than in the services sectors. This appears somewhat surprising in that it would have been fairly reasonable to expect greater internet usage in


275

consumer sectors, such as people services, than in business-to-business ones, such as the majority of the manufacturing industries included in the sample. A possible explanation may be that internet adoption by industrial micro-enterprises has been induced by pressure from larger client-firms that already use this technology. This idea is in line with the empirical evidence of other studies that the decision to introduce internet usage often originates from the external stimulus provided by pressure from clients and suppliers (Fillis and Wagner, 2005; Poon, 2000). The size differential between services and manufacturing firms can provide another explanation for these unexpected results. Regarding the specific industrial sectors, significant differences emerged between the textile, footwear, and other manufacturing sectors on one hand and the woodworking and mechanical sectors on the other, with the latter having the greatest propensity for the internet adoption. In line with the findings of other studies, we found that firm size, measured in terms of the number of employees, constitutes an important (albeit not the most relevant) factor in determining whether or not the internet is adopted as management tool. In contrast, it appears that firm location, in terms of the size of the municipality and its geographical area (coastal or inland area), does not influence internet adoption. This is only partly in line with the findings of other studies. Nevertheless, it is worth highlighting that, in this analysis, the larger cities were not considered separately from other municipalities and that, in the Marche region, there are no metropolitan areas. The non-relevance of firm location, considered along with the relevance of firm size, could be interpreted as an indication that the internal resources of the firm have a greater influence than the external resources on a firm’s internet adoption. A final aspect examined in the study pertains to the degree of openness towards foreign markets and the possible influence this can have on the adoption of web-based tools. Empirical evidence provides strong confirmation that firms showing a greater export propensity have a greater probability of adopting internet technology. One possible explanation could be that those firms manifesting a greater degree of internationalisation also present more complex information and management needs than others and thus have a more powerful incentive to utilise the internet as a management tool. Some interesting issues arose from the cluster analyses regarding the different purposes of using the internet and the tools implemented (part II of research). It seems there exists three types of companies with a very different degree of ‘openness’ to the internet and different use of digital communication tools. The majority of firms were grouped in cluster 3 of low-end internet users. They approach marketing and communication with a very traditional logic and likely they do not have the necessary skills to enhance their businesses with internet use. Firms in cluster 3 seem aware of but are not yet actively using the most innovative tools. Only firms in cluster 2, that is high-end internet users, seem to have reached a certain maturity regarding e-business, but these firms represent only 9.5% of the sample. Given these results, it appears that the micro-enterprises have achieved an ‘unaccomplished modernity’; i.e., they have not yet fully grasped what the internet potentially has to offer. On one hand, only a minority has internet connectivity; on the other hand, the firms that have this connectivity must overcome the traditional and simplistic approach that characterises their current usage of the internet and to encompass a more well-structured and diversified approach.

276

F. Pascucci et al.

Especially in smaller businesses, the role played by the entrepreneur is frequently a determining one in many, if not most, of the strategic decisions and therefore in those decisions relative to the adoption of new technologies too. The growth of a micro-enterprise (in terms of enrichment of competences and abilities) and the characteristics of the entrepreneur are strictly interdependent. For example, the study findings confirm that entrepreneur age is a relevant factor. Those firms with younger entrepreneurs fall into clusters 2 and 3, showing greater propensity for use of the internet and implementation of online marketing tools. In terms of policy implications, firms that do not take advantage of internet tools lost business opportunities as recognised recently by European Commission News (2016), which declared that ‘Digital transformation is not an option – it is a must’. Various studies have shown that using the internet can contribute to the international expansion of enterprises, particularly smaller ones. In addition, not all MEs need to be connected in the global world through the internet because of their local business scope. For these firms, traditional word-of-mouth and personal relationships are more effective. To fill the existing digital divide between MEs and larger businesses, the cultural divide must be bridged. In this sense, associations and governments play a major role in the provision of an internet-related skills-based workforce and practical support. There are many international project to improve ICT in these types of enterprises (see Small Business Act) and to develop a digital culture even in traditional sectors. However, the actual results are not yet satisfactory both in developed and in emerging countries, perhaps because they fail to take into account the differences that exist among SMEs of different sizes. Another important practical implication pertains the necessity to not divide support to digitalisation from support to internationalisation. These two topics are in general faced separately (both in the policy and in the research contexts) and they are not treated as part a common way for the MEs development. The analysis presents some limitations, including the fact that only the age of the entrepreneur was taken into consideration as a determinant factor of internet usage while neglecting other personal skills. This could provide an interesting topic for future research. Another possibility for future consideration is a benchmarking analysis from different points of view, such as cross-country (developed vs. emerging countries) and cross-dimensional. Looking at the methodology, the study measures internet usage through a binary variable. However, the implementation of a measurement scale could offer more relevant information about the intensity of internet usage. Moreover, a limitation of the logistic regression model is that, if there are a high number of predictors, the interpretation of the findings obtained could become complex.

References Abed, S., Dwivedi, Y. and Williams, M. (2015) ‘Social media as a bridge to e-commerce adoption in SMEs: a systematic literature review’, The Marketing Review, Vol. 15, No. 1, pp.39–57. Alderete, M.V. (2014) ‘ICT incidence on the entrepreneurial activity at country level’, International Journal of Entrepreneurship and Small Business, Vol. 21, No. 2, pp.183–201.


277

Al-Qirim, N. (2007) ‘The adoption of eCommerce communications and applications technologies in small businesses in New Zealand’, Electronic Commerce Research and Applications, Vol. 6, No. 4, pp.462–473. Arbore, A. and Ordanini, A. (2006) ‘Broadband divide among SMEs: the role of size, location and outsourcing strategies’, International Small Business Journal, Vol. 24, No. 1, pp.83–99. Barnes, D., Clear, F., Dyerson, R., Harindranath, G., Harris, L. and Rae, A. (2012) ‘Web 2.0 and micro-businesses: an exploratory investigation’, Journal of Small Business and Enterprise Development, Vol. 19, No. 4, pp.687–711. Bayo-Moriones, A. and Lera-Lopez, F. (2007) ‘A firm-level analysis of determinants of ICT adoption in Spain’, Technovation, Vol. 27, No. 6, pp.352–366. BCG Perspectives (2013) Unlocking the Digital-Marketing Potential of Small Businesses. Bengtsson, M., Boter, H. and Vanyushyn, V. (2007) ‘Integrating the internet and marketing operations: a study of antecedents in firms of different size’, International Small Business Journal, Vol. 25, No. 1, pp.27–48. Bordonaba-Juste, V., Lucia-Palacio, L. and Polo-Redondo, Y. (2012) ‘The influence of organizational factors on e-business use: analysis of firm size’, Marketing Intelligence and Planning, Vol. 30, No. 2, pp.212–229. Brown, D.H. and Kaewkitipong, L. (2009) ‘Relative size and complexity: e-business use in small and medium sized tourism enterprises in Thailand’, Journal of Enterprise Information Management, Vol. 22, Nos. 1/2, pp.212–231. Burke, K. (2005) ‘The impact of firm size on internet use in small businesses’, Electronic Markets, Vol. 15, No. 2, pp.79–93. Burke, K. (2013) ‘ICTs in the micro-enterprise: an examination of usage, benefits and firm growth in Hawaii’s agricultural sector’, in Nasir, S. (Ed.): Modern Entrepreneurship and E-Business Innovation, IGI Global. Caniëls, M.C.J., Lenaerts, H.K.L. and Gelderman, C.J. (2015) ‘Explaining the internet usage of SMEs: the impact of market orientation, behavioural norms, motivation and technology acceptance’, Internet Research, Vol. 25, No. 3, pp.358–377. Chatzoglou, P. and Chatzoudes, D. (2016) ‘Factors affecting e-business adoption in SMEs: an empirical research’, Journal of Enterprise Information Management, Vol. 29, No. 3, pp.1–46. Cheung, W.M. and Huang, W. (2002) ‘An investigation of commercial usage of the World Wide Web: a picture from Singapore’, International Journal of Information Management, Vol. 22, No. 5, pp.377–388. Chua, A., Deans, K. and Parker, C.M. (2009) ‘Exploring the types of SMEs which could use blogs as a marketing tools: a proposed future research agenda’, Australasian Journal of Information Systems, Vol. 16, No. 1, pp.117–137. Ciambotti, M., Demartini, P. and Palazzi, F. (2012) ‘The rise of medium-sized enterprises in Europe beyond the dualist model: small vs. large firms’, Journal of Marketing Development and Competitiveness, Vol. 6, No. 3, pp.83–94. Clark, D.N. and Douglas, H. (2011) ‘Information and communication technology adoption and diffusion in micro-enterprises: the case of techno-savvy home-based businesses’, International Journal of Entrepreneurship and Small Business, Vol. 14, No. 3, pp.349–368. Dana, L.P. (2008) Handbook of Research on European Business and Entrepreneurship towards a Theory of Internationalization, Edward Elgar Publishing, Northampton, USA. Dana, L.P. and Wright, R.W. (2009) ‘International entrepreneurship: research priorities for the future’, International Journal of Globalisation and Small Business, Vol. 3, No. 1, pp.90–134. Dandridge, T. and Levenburg, N.M. (2000) ‘High-tech potential? An exploratory study of very small firms’ usage of the Internet’, International of Small Business Journal, Vol. 18, No. 2, pp.81–91.

278

F. Pascucci et al.

Davis, C.H. and Vladica, F. (2006) ‘Use of internet technologies and e-business solutions: a structural model of sources of business value among Canadian micro-enterprises’, Proceedings of the 39th Hawaii International Conference on System Science. Davis, P.S. and Harveston, P.D. (2000) ‘Internationalization and organizational growth: the impact of Internet usage and technology involvement among entrepreneur-led family business’, Family Business Review, Vol. 13, No. 2, pp.107–120. Dholakia, R.R. and Kshetri, N. (2004) ‘Factors impacting the adoption of the internet among SMEs’, Small Business Economics, Vol. 23, No. 4, pp.311–322. Drennan, J. and McColl-Kennedy, J.R. (2003) ‘The relationship between internet use and perceived performance in retail and professional service firms’, Journal of Service Marketing, Vol. 17, No. 3, pp.295–311. Durkin, M., McGowan, P. and McKeown, N. (2013) ‘Exploring social media adoption in small to medium-sized enterprises in Ireland’, Journal of Small Business and Enterprise Development, Vol. 20, No. 4, pp.716–734. Dutta, S. and Evrard, P. (1999) ‘Information technology and organization within European small enterprises’, European Management Journal, Vol. 17, No. 3, pp.239–251. Etemad, H., Wilkinson, I. and Dana L.P. (2010) ‘Internetization as the necessary condition for internationalization in the newly emerging economy’, Journal of International Entrepreneurship, Vol. 8, No. 4, pp.319–342. European Commission (2014) A Partial and Fragile Recovery, Directorate General for Enterprise and Industry, Annual Report on European SMEs 2013/2014. European Commission News (2016) Digital Transformation is Not an Option – It Is a Must, Published 11 March 2016 [online] http://ec.europa.eu/growth/news/index_en.htm?tpa=1044 (accessed 27 April 2016). Fillis, I. and Wagner, B. (2005) ‘E-business development: an exploratory investigation of the small firm’, International of Small Business Journal, Vol. 23, pp.604–634. Fillis, I., Johannson, U. and Wagner, B. (2004) ‘Factors impacting on e-business adoption and development in the smaller firm’, International Journal of Entrepreneurial Behavior and Research, Vol. 10, No. 3, pp.178–191. Gërguri-Rashiti, S., Ramadani, V., Abazi-Alili, H., Dana, L. and Ratten, V. (2015) ‘ICT, innovation and firm performance: the transition economies context’, Thunderbird International Business Review, DOI: 10.1002/tie.21772. Gilmore, A., Gallagher, D. and Henry, S. (2007) ‘E-marketing and SMEs: operational lessons for the future’, European Business Review, Vol. 19, No. 3, pp.234–247. Hairuddin, H., Noor, N.L.M. and Malik, A.M.A. (2012) ‘Why do microenterprise refuse to use information technology: a case of Batik microenterprises in Malaysia’, International Conference on Asia Pacific Business Innovation and Technology Management, in Procedia – Social and Behavioural Sciences, Vol. 57, pp.494–502. Hanafizadeh, P., Behboudi, M., Ahadi, F. and Varkani, F.G. (2012) ‘Internet advertising adoption: a structural equation model for Iranian SMEs’, Internet Research, Vol. 22, No. 4, pp.499–526. Hashim, N.H., Murphy, J., Purchase, S. and O’Connor, P. (2010) ‘Website and e-mail adoption by Malaysian hotels’, International Journal of Hospitality Management, Vol. 29, No. 1, pp.194–196. Hollestein, H. (2004) ‘Determinants of the adoption of information and communication technologies. An empirical analysis based on firm-level data for the Swiss business sector’, Structural Change and Economic Dynamics, Vol. 15, No. 3, pp.315–342. Istat (2015) Rapporto Annuale: La situazione del Paese [online] http://www.istat.it/it/archivio/ 159350 (accessed 8 February 2016). Johnston, D.A., Wade, M. and McClean, R. (2007) ‘Does e-business matter to SMEs? A comparison of the financial impacts of internet business solutions on Europe and North American SMEs’, Journal of Small Business Management, Vol. 45, No. 3, pp.354–361.


279

Jones, P., Packham, G., Beynon-Davies, P. and Pickernell, D. (2011) ‘False promises: e-business deployment in Wales’ SME community’, Journal of Systems and Information Technology, Vol. 13, No. 2, pp.163–178. Jones, P., Simmons, G., Packham, G. and Pickernell, D. (2014) ‘An exploration of the attitude and strategic responses of sole-proprietor micro-enterprises in adopting information and communication technology’, International Small Business Journal, Vol. 32, No. 3, pp.285–306. Kelliher, F. and Reinl, L. (2009) ‘A resource-based view of micro-firm management practice’, Journal of Small Business and Enterprise Development, Vol. 16, No. 3, pp.521–532. Kim, H.D., Lee, I. and Kwon Lee, C. (2011) ‘Building Web 2.0 enterprises: a study of small and medium enterprises in the United States’, International Small Business Journal, Vol. 31, No. 2, pp.156–174. Kula, V. and Tatoglu, E. (2003) ‘An exploratory study of internet adoption by SMEs in an emerging market economy’, European Business Review, Vol. 15, No. 5, pp.324–333. Levenburg, N.M. (2005) ‘Does size matters? Small firms’ use of e-business tools in the supply chain’, Electronic Markets, Vol. 15, No. 2, pp.94–105. Love, P.E.D., Irani, Z., Standing, C., Lin, C. and Burn, J.M. (2005) ‘The enigma of evaluation: benefits, costs and risks of IT in Australian small-medium-sized enterprises’, Information and Management, Vol. 42, No. 7, pp.947–964. MacGregor, R. and Vrazalic, L. (2005) ‘A basic model of electronic commerce adoption barriers’, Journal of Small Business and Enterprise Development, Vol. 12, No. 4, pp.510–527. Nakara, W.A., Benmoussa, F. and Jaouen, A. (2012) ‘Entrepreneurship and social media marketing: evidence from French small business’, International Journal of Entrepreneurship and Small Business, Vol. 16, No. 4, pp.386–405. Nobre, H. and Silva, D. (2014) ‘Social network marketing strategy and SME strategy benefits’, Journal of Transnational Management, Vol. 19, No. 2, pp.138–151. Oliveira, T. and Martins, M.F.O. (2008) ‘A comparison of web site adoption in small and large Portuguese firms’, ICE-B 2008: Proceedings of the International Conference on E-Business, pp.370–377, Porto. Parker, C.M. and Castleman, T. (2007) ‘New directions for research on SME-eBusiness: insights from an analysis of journal articles from 2003 to 2006’, Journal of Information Systems and Small Business, Vol. 1, Nos. 1–2, pp.21–40. Peltier, J.W., Zhao, Y. and Schibrowsky, J.A. (2012) ‘Technology adoption by small businesses: an exploratory study of interrelationships of owner and environmental factors’, International Small Business Journal, Vol. 30, No. 4, pp.406–431. Pontikakis, D., Lin, Y. and Demirbas, D. (2005) ‘History matters in Greece: the adoption of internet-enabled computers by small and medium sized enterprises’, Information Economics and Policy, Vol. 18, pp.332–358. Pontikakis, D., Lin, Y. and Demirbas, D. (2006) ‘History matters in Greece: the adoption of internet-enabled computers by small and medium sized enterprises’, Information Economics and Policy, Vol. 18, No. 3, pp.332–358. Poon, S. (2000) ‘Business environment and internet commerce benefits – small business perspective’, European Journal of Information Systems, Vol. 9, No. 2, pp.72–81. Premkumar, G. and Roberts, M. (1999) ‘Adoption of new information technologies in rural small business’, Omega, Vol. 27, No. 4, pp.467–484. Putra, P.O.H. and Hasibuan, Z.A. (2015) ‘The relationship between enterprise internationalization and e-business adoption: a perspective of Indonesian SMEs’, 2015 International Conference on Information Society (i-Society), pp.122–126, IEEE. Reid, G.C. (1995) ‘Early life-cycle behaviour of micro-firms in Scotland’, Small Business Economics, Vol. 7, No. 2, pp.89–95. Rogers, E.M. (1995) Diffusion of Innovations, The Free Press, New York.

280

F. Pascucci et al.

Santarelli, E. and D’Altri, S. (2003) ‘The diffusion of e-commerce among SMEs: theoretical implications and empirical evidence’, Small Business Economics, Vol. 21, No. 3, pp.273–283. Setiawan, M., Indiastuti, R. and Destevanie, P. (2015) ‘Information technology and competitiveness: evidence from micro, small and medium enterprises in Cimahi District, Indonesia’, International Journal of Entrepreneurship and Small Business, Vol. 25, No. 4, pp.475–493. Simmons, G., Armstrong, G.A. and Durkin, M.G. (2008) ‘A conceptualization of the determinants of small business website adoption: setting the research agenda’, International Small Business Journal, Vol. 26, No. 3, pp.351–386. Solaymani, S., Sohaili, K. and Yazdinejad, E.A. (2012) ‘Adoption and use of e-commerce in SMEs’, Electronic Commerce Research, Vol. 12, No. 3, pp.249–263. Stansfield, M. and Grant, K. (2003) ‘An investigation into issues influencing the use of the internet and electronic commerce among small-medium sized enterprises’, Journal of Electronic Commerce Research, Vol. 4, No. 1, pp.15–33. Tan, K.S., Chong, S.C., Lin, B. and Eze, U.C. (2009) ‘Internet-based ICT adoption: evidence from Malaysian SMEs’, Industrial Management and Data Systems, Vol. 109, No. 2, pp.224–244. Tan, K.S., Chong, S.C., Lin, B. and Eze, U.C. (2010) ‘Internet-based ICT adoption among SMEs. Demographic versus benefits, barriers, and adoption intention’, Journal of Enterprise Information Management, Vol. 23, No. 1, pp.27–55. Thapa, A. (2015) ‘Determinants of microenterprise performance in Nepal’, Small Business Economics, Vol. 45, No. 3, pp.581–594, DOI: 0.1007/s11187-015-9654-0. The Boston Consulting Group (2012) The Internet Economy in the G-20. The Boston Consulting Group (2013) SME Internet E-Friction Survey. Toninelli, P.A. and Vasta, M. (2014) ‘Opening the black box of entrepreneurship: the Italian case in a historical perspective’, Business History, Vol. 56, No. 2, pp.161–186. Tornatzky, L. and Fleischer, M. (1990) The Process of Technology Innovation, Lexington Books, Lexington, MA. Van Beveren, J. and Thomson, H. (2002) ‘The use of electronic commerce by SMEs in Victoria, Australia’, Journal of Small Business Management, Vol. 40, No. 3, pp.250–253. Varadarajan, R. and Yadav, M.S. (2009) ‘Marketing strategy in an internet-enabled environment: a retrospective on the first ten years of JIM and a prospective on the next ten years’, Journal of Interactive Marketing, Vol. 23, No. 1, pp.11–22. Varaldo, R., Dalli, D., Resciniti, R. and Tunisini, A. (Eds.) (2009) Un tesoro emergente. Le medie imprese italiane dell’era globale, Franco Angeli, Milan. Voges, K.E. and Pulakanam, V. (2011) ‘Enabling factors influencing internet adoption by New Zealand small and medium size retail enterprises’, International Review of Business Research Papers, Vol. 7, No. 1, pp.106–117. Wade, M., Johnston, D. and McClean, R. (2004) ‘Exploring the net impact of internet business solution adoption on SME performance’, International Journal of Electronic Business, Vol. 2, No. 4, pp.336–350. Wolcott, P., Kamal, M. and Qureshi, S. (2008) ‘Meeting the challenges of ICT adoption by micro-enterprises’, Journal of Enterprise Information Management, Vol. 21, No. 6, pp.616–632.

Notes 1

Information sheet Small Business Act For Europe 2012 – Italy.