Internal and External Success Factors for Implementation of
E-Business by SMEs in the North Netherlands
by
Dennis Dikkerboom
University of Groningen
Faculty of Economics and Business
MScBA Operations & Supply Chains
ABSTRACT
De Ontwikkelfabriek BV, a service provider of internet solutions, tries to understand why its small and medium-sized customers tend to have a lack of understanding with regard to the risk, barriers, leverages surrounding the implementation of e-business while it has so much potential to create value for these businesses. Thus, the company would like to know which when e-business is likely to be successful, under which circumstances small and medium-sized companies are willing to make the decision to implement it and how the company can play a role to realise this.
The theory on diffusion on innovations shows that while small and medium-sized businesses are important in disseminating an innovation in a social system, their
characteristics form an obstacle by negatively influencing the trade-off between the value and risk involved with implementing such a technology. Further literature explains that these businesses could be effected on a macro, meso and micro level, including in the areas of eco-impact, supply chains, strategy and operations.
Rank correlation analysis using the results of a survey held amongst 226 small and medium-sized enterprises and with a return rate of 8% shows that the risk of
implementing e-business has significant and negative influence on the decision-making process, while the value of e-business does not seems to have a significant effect. Furthermore, governmental subsidies and the adoption rate of e-business by substitute positive significantly effect the decision to implement e-business, while the current economic incertitude has a negative significant influence.
To conclude, de Ontwikkelfabriek BV could play a supportive role in creating awareness with regard to the availability of governmental support or the capability of the IT
PREFACE
This thesis, as a part of the Master of Science Business Administration Operations & Supply Chains, has been a long, but interesting journey. When I started somewhat more than year ago, I could never have guessed how windy the road would be. In fact, I did not even know where it would take me and where I would end up. While there have been plenty of obstacles down the way and there would have been a much easier path to the final destination, the road that has led me has taught me so much more than presented in this thesis.
I would like to thank prof. dr. Kamann and dr. Broekhuis for providing me with guidance on how to proceed and helping me in deciding which directions to take. Without it, I would certainly have ended up in St. Petersburg. I also would like to thank Peter van Kampen and Erik Douma for keeping me on track and encouraged. Without it, the journey would have taken twice as long. Special thanks for my family and friends for supporting me in their own fashion and style and giving me hope when facing
difficulties. Without it, there definitely was a possibility I would have given up.
1. INTRODUCTION
In recent years the usage of internet has experienced a dramatic expansion. While in 1997 the internet penetration rate was only 11 per cent of the developed world population, this number has risen to 62 per cent within a decade (International Telecommunication Union, 2007). In 2008, 86 per cent of the Dutch households had access to internet and almost nine-tenths of these households had a broadband connection (Centraal Bureau voor de Statistiek, 2009a).
Online shopping has shown a similar growth pattern recently. In 2008, nearly one third of the individuals between 16 and 74 had bought or ordered a product or service online. This signified an increase of 12 percentage points or 60 per cent since 2004 (Eurostat, 2009). Especially large and manufacturing organisations benefit from this development. On one side, in large organisations on average 15 per cent of the total sales is accounted for by online sales, while in the smallest businesses this accounts for only 6 per cent of the sales. On the other side, the figure of sales representation reaches between 15 and 20 per cent in manufacturing organisations against 3 per cent in professional services (Centraal Bureau voor de Statistiek, 2008). Of course, it must be noted that these figures will strongly vary between industrial sectors and individual organisations. However, in general, the
percentage in sales value represented by sales performed online is estimated to have more than quadrupled between 1999 and 2007.
Furthermore, e-business is acknowledged by numerous authors, such as Amit & Zott (2001), Barua et al. (2001), Damanpour & Damanpour (2001) and Lee & Whang (2001), for creating value for organisations in many different ways. Examples of such added value can be increased efficiency, operational excellence, improved supply chain
willingness of smaller sized organisations to adopt e-business in fear of not being able to keep up with the competition (Abrahamson & Rosenkopf, 1993). However, such a motive as the main force behind the implementation of e-business may lead to poor results, because it is mostly based on normative pressure instead of economic reasoning (Wu, Mahajan & Balasubramanian, 2003).
Therefore, the choice for e-business should be a deliberate decision, in which the risks and the added value of e-business are weighed upon each other. In order to take a
decision with such implications, an organisation should be aware of the main internal and external factors that influence a successful, value adding implementation of e-business. However, for small and medium-sized enterprises this may be difficult. The barriers for successful implementation of IT in such organisations often include the lack of
knowledge with regard to IT and a lack of understanding concerning the measurement of the benefits (Burgess, 2002). Because of these barriers it is important for small and medium-sized enterprises to obtain useful and impartial advice.
De Ontwikkelfabriek BV is a service provider of internet solutions. Its services include developing and researching innovative concepts for small and medium-sized enterprises as well as advising and supporting clients in using internet in the most optimal way. The management of de Ontwikkelfabriek BV feels that small and medium-sized enterprises in the North Netherlands could be much more active in tapping into the potential of e-business. Although the company recognizes these businesses are faced with a wide range of barriers, it struggles to make a precise distinction between actual and supposed
problems. Therefore, de Ontwikkelfabriek BV feels that in order to give potential customers a more thorough advice on these issues, the company needs to have a deeper understanding of the underlying factors influencing the successful implementation of e-business in small and medium-sized enterprises.
1.1 Problem statement
medium-sized enterprises in the North Netherlands tends to create business value. This will enable de Ontwikkelfabriek BV to give similar enterprises more scientific grounded advice concerning the decision-making process with regard to the implementation of e-business solutions.
To accomplish this goal, the main research question of this paper will be the following: Which internal and external risks and barriers and which internal and external leverages are crucial in the decision-making process with regard to the implementation of
successful, in terms of value-adding, e-business in small and medium-sized enterprises located in the North Netherlands?
1.2 Definitions of key elements
In order to conduct a proper research, it is essential to define three key elements in the main research question: the population, the innovation and the success factor. So, it can be made clear which type of organisations and what form of online business will be researched as well as which measurement of success will be used.
1.2.1 Population
While small businesses are immensely diverse, it is necessary to aim for the highest level of generalisation in order to avoid a too complex environment (Nooteboom, 1994). The research population – focusing on a specific group of businesses – is defined according to five different limitations being size, location, industry sector, supply chain role, and consumer value. The choices that have been made with regard to these limitations will be discussed below, including a statistical representation.
First of all, the research will exclude large companies, for de Ontwikkelfabriek BV purely focuses on small and medium-sized enterprises as its customers. These SMEs are
approach. As is customary in The Netherlands, does de Ontwikkelfabriek BV use a typology of small, medium and large companies with respectively less than 10
employees, between 10 and 100 employees, and more than 100 employees (Kloek, 2002).
TABLE 1: Specifications of 2003 EC enterprise definition
Enterprise category Number of employees Turnover Balance sheet total
Micro < 10 ≤ € 2 million ≤ € 2 million Small < 50 ≤ € 10 million ≤ € 10 million Medium < 250 ≤ € 50 million ≤ € 43 million
Secondly, the research will only include the service area of de Ontwikkelfabriek BV by focusing only on manufacturing businesses in the North Netherlands. Manufacturing is, according to the industrial classification system used in The Netherlands (Standaard Bedrijfsindeling, SBI), an industrial branch mostly including businesses focusing on production and assembly. The North Netherlands is a first level Nomenclature of
Territorial Units for Statistics (NUTS or nomenclature d'unités territoriales statistiques) region in The Netherlands consisting of the three northern located provinces of Fryslân, Groningen and Drenthe (European Commission, 2007).
Thirdly, the research will focus on products which requirements can be electronically specified in a verifiable manner. Products with such high levels of codability are more likely to be successful in e-business (Kleindorfer & Wu, 2003). Fourthly, the paper will also have a research focus on companies located more downstream of the supply chain, for those companies not only are more likely to be manufacturing businesses, but also are more likely to produce highly codable products. To conclude, the research will focus on a population with a strong possibility to implement e-business and thus would be more likely to be possible clients for de Ontwikkelfabriek BV.
voor de Statistiek, 2009c).
1.2.2 Innovation
E-Business is a concept of integrating the capabilities of internet and likewise
technologies into business processes. Earl (2000) had indentified a six-stage evolution of this concept with in each stage an increased level in the use online applications within the key processes of a business. The first two stages focus on using internet to communicate both externally as internally, by means of the use of e-mail and websites. The third stage implies the buying and selling of products or services online and the fourth stage has as goal to re-engineer the business processes and to integrate the supply chain. The last two stages focus on performing management processes as decision-making online and on becoming a dynamic and open system by continuous innovation. These six stages and their main objectives are portrayed in figure 1.
FIGURE 1: Stages in e-business evolvement
Corporate homepage Buying or selling online Corporate Intranet Adding key capabilites Decision by wire Let’s drop the “E”
Stage I Stage II Stage III Stage IV Stage V Stage VI
Based on Figure 1: Evolving the E-Enterprise (Earl, 2000)
Martin & Matlay (2001) have a similar five-step classification called the DTI adaption ladder in which the last two stages of the evolution are integrated. In this paper, following the definition of de Ontwikkelfabriek BV with regard to e-business, it is seen as at least trading goods and services online, as described in the third stage.
Value-adding is a process in which, from a business point of view, the value a specific stakeholder attributes to a company is increased. However, with several types of stakeholders – such as suppliers, customers, shareholders, and employees (Freeman, 1984) – and several definitions for the term value – such as value as price, value as utility, value as trade-off, and value as evaluation (Zeithaml, 1988) – this quickly becomes quite vague. This research will focus mainly on the value e-business yields for the shareholders – in most small and medium-sized enterprises, the owner – of the company. Furthermore, value will be defined by the term utility (Zeithaml, 1988). More specifically in this case, it is both the reduction in operations costs and the increment in revenues through the introduction of e-business. For it is expected that traditional operational excellence measures – such as inventory turnover and order delivery cycle time – as well as financial consumer measures – such as profitability and geographical reach – improve with the implementation of e-business (Barua et al., 2001; Christensen & & Methlie, 2003).
1.3 Research strategy
The research is a combination of explorative and empirical testing research. In a literature research the risks, barriers and leverages with regard to the success of e-business were investigated. The goal of this part was to construct a conceptual model and to formulate a series of hypotheses on the success factors. These hypotheses were tested by means of a survey which was distributed to numerous small and medium-sized businesses in the research population. From this analysis the research has drawn conclusions on the importance of each factor on the decision-making process and further made a few recommendations on the role de Ontwikkelfabriek BV could play in enabling small and medium-sized companies to overcome obstacles. Each phase in this short overview of the research strategy and structure will be more precisely explained below.
In the first phase the research first looked into the theoretical basis for the stated
influencing the success of e-business which especially focused on the decision-making process (Fillis, Johannson & Wagner, 2004). This model was used not only as a starting point from where different elements would be further investigated, but also gave structure to this following phase of discussing probable variables. Each of the aggregated levels were researched within well-known frameworks, such as DESTEP (Nijenhuis, 2007) and the five forces model (Porter, 1979) using the extensive literature found in the leading research databases of EBSCO, Emerald Insight and Elsevier. The review focused on literature in the field of business administration and management science in general and in the field of small business and computer science specifically.
In the second phase, the research formulated hypotheses a series of hypotheses from the previously discussed factors. For most of the investigated articles had a focus on a few specific influences on e-business, the findings from this literature could be rewritten into suppositions without too much difficulty. Furthermore, the concepts within the
formulated hypotheses were used to build a conceptual model to give a visual representation of the assumed relationships as stated in the suppositions.
In the third phase, the variables within the conceptual model were operationalised. From this operationalisation, each relationship from the conceptual model was translated into a series of valid and reliable investigative questions within in a survey. This questionnaire was sent to a set of small and medium-sized companies within the research population in order to gain in-field data on the experienced risk, barriers and leverages among these businesses on the decision-making process with regard to the implementation of e-business. Then, this self-reported data was analysed and consequently used to test the formulated hypotheses in order to see if the influences found in the literature research actually affected these types of businesses.
2. LITERATURE REVIEW
This section will discuss the literature on factors influencing the success of e-business in small and medium-sized enterprises. Firstly, it will look into the arguments of small and medium-sized enterprises considering implementing e-business and its resulting
difficulties by explaining the diffusion of innovations theory in the light of small businesses. Secondly, a proposed conceptual model will be presented and discussed in order to give an overview of the various factors affecting the adoption of e-business and to present the structure within these factors. Thirdly, the section will further investigate each level of aggregation by discussing several articles on the various kinds of
influencing factors to give a thorough image of existing literature in this field. Fourthly, the practical applicability of the given theories within small and medium-sized business in the North Netherlands will be discussed. Lastly, several hypotheses on the influencing factors will be formulated and consequently a conceptual model will be built.
2.1 Diffusion of innovations
In order to give insight in the possible factors influencing the success of e-business within small and medium-sized business, it is necessary to explain the theoretical basis of the processes underlying the adoption of an innovation. The introduction already has given some answers by explaining that bandwagon effects can be one of the reasons smaller businesses are more willing to make use of business. Furthermore, while defining e-business, this paper has also discussed the evolution of this technology from a
classification perspective. However, this clearly does not present the complete picture.
Schumpeter (1943) explains that small businesses can play an innovative role in so-called creative destruction. That is, the concept of using innovation as the force behind
economic growth in which fundamental improvement could only occur by radical change, even at the cost of destroying the value of established organisations. However, Schumpeter (1943) also notes that only large companies and concentrated markets can produce innovation. Nooteboom (1994) clarifies this contradiction by giving the
of innovations stem from larger corporations, the small and medium-sized enterprises are still very important in differentiating and adapting it for their specific operations and markets and thereby disseminating the innovation in a social system.
FIGURE 2: Stages of innovation
Adopted from Figure 1: Stages of innovation (Nooteboom, 1994)
Rogers (1983) has further explained this process known as diffusion by formulating the different steps in adopting the innovation by new users as presented in figure 3. The adoption processes follows the sequence from being aware that an innovation is available and being convinced that the innovation can be useful to deciding if the innovation will be implemented, the process of implementing itself and the conformation that the innovation has resulted in the expected progress.
FIGURE 3: Stages of adoption
Adopted from Figure 2: Stages of adoption (Nooteboom, 1994)
explains that smaller companies can apply an innovation to their organisation in a better fashion due to the high levels of tacit knowledge, but also that this lack of precise knowledge can form an obstacle in the first stages of the model of Rogers (1983). Furthermore, it can also affect the trade-off between the risks and the revenues and thus negatively influence the decision-making process for small organisations. Nooteboom (1994) explains that external contacts can help overcome these obstacles by giving more explicit and formal information on the problems and the opportunities smaller business could face. Therefore, it is necessary to look into the more precise barriers and leverages which affect the decision regarding the innovation of e-business in small and medium-sized enterprises.
2.2 Overview of factors
According to an article by Fillis, Johannson & Wagner (2004), there is a wide range of factors on different levels that influence the development of e-business in smaller businesses. On a macro level, the article shows that there are quite large differences on adoption rates between countries and regions, which may be assigned to cultural differences or governmental policy. On a meso level, it explains that the smaller size of an organisation can both have benefits and drawbacks with regard to the implementation of technology. The most important advantage lies in the ability to be flexible, while the most important disadvantages are the time and effort consumed in introducing new technology within the company. Besides that, the article also explains that the need to implement e-business is related to the industry sector a company belongs to. For example, the level of benefits that improved communications with stakeholders entail, differs between industry sectors
Furthermore, on a micro level, Fillis, Johannson & Wagner (2004) see that organizational and managerial elements of a smaller organisation, like structure and procedures, can form a barrier to innovate. Especially if in such organisations, due to the small number of employees, the decision-making is centralised towards one person. Moreover, the
overcome traditional barriers smaller businesses face. Finally, on a personal level, the authors make clear that in smaller firms, that the attitude of the employees, especially that of the owner, towards e-business has a great effect on the level of e-business adoption. According to the article, the philosophy of the owner on the need to introduce e-business is affected by the macro, meso and micro levels and ultimately forms the decision of (non-)adoption.
The article by Fillis, Johannson & Wagner (2004) gives some very important thoughts on influencing factors. The article has an evaluative point of view on the influencing factors and in terms of the adoption stages by Rogers (1983), it can be said that it focuses on the decision stage. Furthermore, it is important to note that the article presents the macro, meso and micro level as being presented as being subordinate to the personal level. This view is supported by literature on decision making processes. Eisenhardt & Zbaracki (1992) conclude that strategically making a decision is based on both bounded rationality and business politics. They explain that to make a decision is bounded rational due to the cognitive limits – such as intuition and emotion – of decision makers and it is political due to the fact that the most powerful figures in an organization determine decisions. However, Eisenhardt & Zbaracki (1992) also advocate for a broad view on the decision making process. Therefore, with the limitations of this research, it would be interesting to look specifically into the different elements of the macro, meso and micro levels and to see which specific parts of these different levels are particular of influence on the decision to implement e-business.
2.3 Factors on a macro level
2.3.1 Population characteristics
Demographics – derived from the Greek words of dèmos meaning people and graphoo meaning to describe – are the characteristics of a population used by statistics and
research in order to form segments within this population and to give an overall picture of a member within one of these segments. Typical and commonly used demographics include factors such as gender, age, descent and civil state (Centraal Bureau van de Statistiek, 2009d). There is a wide rang of economic research on the effects of these demographics on several aspects business performance, including research areas such as ethics (Ruegger & King, 1992), formation and establishment (Evans & Leighton, 1990), and marketing (Zeithaml, 1985).
Research on the effects of the population characteristics on technology in general has indicated that factors like gender, income, age, and education are significant influences on the use of this technology (Dickerson, & Gentry, 1983; Igbaria, Iivari & Maragahh, 1995). However, most investigations focus on the influences of demographics within a personal situation instead of a business situation. This nullifies the effects of income on the choice to adopt e-business. Furthermore, Kotter & Schlesinger (1979) show that the ability to change mostly affects the resistance to change, rather than influencing the process itself. Thus, this influence will not be further investigated.
2.3.2 Current economic state
It is quite obvious that the financial crisis of 2007-2009 and the subsequent recession (The New York Times, 2009) have had and still have their effect on the management of businesses in general. While according to popular acclaim the recession may be over (Norris, 2009), with enormous unemployment rates (Goodman, 2009) and fluctuating consumer confidence (The Associated Press, 2009) the timeline of economic recovery is still uncertain. Studies of earlier recessions have given an idea how entrepreneurs have responded in similar situations with incertitude on the prospects for the following months.
Mukhtar (1994) as mentioned in a study by Hoffman et al (1998). The findings focus in particular on the dichotomy between a reserved attitude with regard to investments and a profitable business opportunity. It is said that in poor macro-economic conditions such as the recession of the early 1980s innovative small and medium-sized enterprises, for example those in biotechnology, adopted a growth- and risk-averse strategy. Thus, these studies give the indication that during uncertain economic times smaller businesses tend to avoid investments, even if they could give them an advantage after the troublesome periods. Therefore, it can be assumed that not only in the current recession these
companies will adopt the same strategy, but also that other types of companies will likely not be taking risks by investing in technological innovations such as e-business. These considerations lead to the following supposition:
H1: The perceived level of incertitude by the owner of a small or medium-sized
enterprise with regard to the developments and prospects of the economic situation has a negative effect on the choice to implement e-business within that organisation.
2.3.3 Regional and cultural differences
According to Hofstede (1980), culture as collective mental programming differs between nations and is determined by the solution a nation has found for four fundamental
problems. The combination of these solutions forms the subconscious emotions of a nation, known as values. From such cultural research also stems the idea that a group’s culture influences the behaviour of this group (Brislin, 1993), which is affecting many managerial areas, like human resource management (Schneider, 2006), research and development (Nakata & Sivakumar, 1996), and marketing (De Mooij, 1997). For e-business, cultural driven behaviour has an effect on both the consumer side (Chau et al., 2002) and the management side (Van Everdingen & Waarts, 2003).
Netherlands. The average culture of a multinational situated in this country may be equal to the cultural subset of Dutch inhabitants. However, this does not mean that this national culture is shared by all residents or in all regions of The Netherlands (Hofstede, 2002). For example, research on trades unions in the Northern Netherlands shows that its
inhabitants are more likely to be uncertainty avoidant and show collective behaviour than residents of other parts of the country (Hofstede, 2002; Zanen, 2009). When taking into account the effects culture can have on behaviour from both a consumer as a management perspective, it can be assumed that a reserved position with respect to uncertainty can have a negative effect on e-business usage. However, all organisations within the research group are part of the same regional culture and differences between these companies are much more likely to be attributed to the contrast in organisational culture, then to regional differences. Thus, this influence will not be further investigated.
2.3.4 Development in IT
Information technology is currently one of the most rapid changing sectors. Moore’s Law on the number of transistors per circuit still applies (Schaller, 1997) and even can be adapted to the growth rate of internet (Coffman & Odlyzko, 1998; 2001). Technological improvement is making larger amounts of computer power and faster internet available for a reasonable price. These developments have ultimately been the driver for the birth of e-business. However, innovation in the North Netherlands is lagging behind in respect to the country as a whole (Samenwerkingsverband Noord-Nederland, 2007). In 2003, only 6% of the total R&D-expenditures of The Netherlands were spent in the three Northern provinces. This marked only 1.3% of the gross regional product against 1.9% of the gross domestic product. Furthermore, the region scores below average on
measurements like number of worldwide operating highly innovative businesses and level of participation in innovation. With e-business in The Netherlands still not being very mature (Van der Sleen, 2009) and when taking the above into account, one can assume that in the North-Netherlands this innovation is currently not very successful.
difference between technology-in-theory and technology-in-use (Argyris & Schon, 1978). Some researchers, such as Coltman et al. (2000), have estimated that in consumer
markets only 15% of the sales will be represented by e-business. However, with regard to business-to-business markets researchers are much more positive. The prospects of reduction in cost, increases in revenue and opportunities of alliances along with the effects of diffusion of innovations (Rogers, 1983) and network externalities (Katz and Shapiro, 1985) make business more willing to participate in e-business then consumers (Coltman et al., 2000). While large portions of buyers and sellers believe this market will grow, it is still thought that the need for obtaining critical mass is crucial for the success of e-business (Barratt & Rosdahl, 2002).
It seems that the level of expectations with regard to the success of a technology can affect its eventual success in practice in two ways, namely by overestimation and by underestimation. However, these expectations cannot be seen as a technological macro-economic influence, but are much more related to personal and social concepts such as trust. Therefore, it is assumed that while the development in IT can have an effect on possible influences not investigated in this research, such as the personal level mentioned above, on itself it does not have an influence on the decision-making process.
Furthermore, this specific research does not allow for changes in behaviour over time. Thus, this influence will not be further investigated.
2.3.5 Environmental impact
Yi & Thomas (2007) have conducted a large-scale review of numerous research sources – including journal papers, theses, and conferences – on the impact of e-business on the environment. The research showed that the environmental benefits of e-business are derived from a second order effect. That is, the opportunities that spring from the ongoing use of this technology and can be found in increased efficiency and speed of transactions. The negative effects of e-business on the environment are of a first order and include the psychical existence of IT such as resource consumption and carbon emissions used in the production of the hardware used in this technology. While fifteen years ago global
warming was considered the least important of seven environmental problems (Dunlap, 1994), today roughly 60 per cent of the world population is aware of global warming and two-thirds of this group considers it a serious threat to themselves or their family
(Pugliese & Ray, 2009). Thus, reducing human’s impact on carbon emissions can be seen as the most important environmental change of this moment. Therefore, one can assume that the awareness on the supportive role e-business can play in making businesses more environmental sustainable by increasing efficiency and in effect reducing emissions is quite important with regard to the implementation decision. These considerations lead to the following supposition:
H2: The level of awareness by the owner of a small or medium-sized enterprise with regard to the supportive role of e-business in becoming ecological-friendly has a positive effect on the choice to implement e-business within that organisation.
2.3.6 Governmental policy
Governments worldwide have taken initiatives in supporting the introduction of business within their nation’s enterprises and their own organisation. Therefore, e-government has become a quite large subsection within e-business research. Investigations on the adopting process (Layne & Lee, 2001) and the acceptance by citizens (Warkentin et al., 2002; Carter & Bélange, 2005) are endless. However, there are still difficulties with policies focused on this specific business prospect. For example, Corbitt & Al-Qirim (2004) mention issues with too broad set policies, with
medium-sized enterprises about government’s initiatives in e-business.
Jutla, Bodorik & Dhaliwal (2002) have indentified a climate in which proper governmental e-business support for smaller companies can dwell. It includes an
infrastructure on areas like content, regulation, finance and human resources within an e-government led and knowledge based economy. The research suggests that is necessary for policy makers to balance these facilitating components to have an effect on the adoption rates. Therefore, governments should make use of a framework which should include well-defined and rated metrics specific for the country’s situation and a
conceptual model which shows the dynamism of governance processes on e-business.
Research on the effect of government support with regard to the adoption of innovations mostly focuses on the possibility that public funding crowds out private investments. This could have significant meaning, for especially lesser economic developed regions receive such support. For instance, a paper by Almus & Czarnitzki (2003) on the effect on
governmental R&D subsidies on innovation intensity in Eastern Germany shows that organisations in this region receive up to 6 times more public R&D funding than its Western counterpart. The researchers show that there is a significant positive causal effect between receiving funding and innovation intensity. Almus & Czarnitzki (2003) conclude that on average these organisations would spend 4 per cent less on innovation without government support.
Syntens and the executive body of the Ministry of Economic Affairs known as
Agentschap NL. However, one of the most important problems, as stated by Corbitt & Al-Qirim (2004), still seems to be the lack of awareness with small companies on these supportive initiatives taken by government. These considerations lead to the following supposition:
H3: The level of awareness by the owner of a small or medium-sized enterprise with regard to possibilities for governmental subsidies supporting e-business has a positive effect on the choice to implement e-business within that organisation.
2.4 Factors on a meso level
The meso environment of an organisation is often described using the five forces model of Porter (1979). That is, a quintuplet of factors – namely the bargaining power of customers, the bargaining power of suppliers, the threat of new entrants, the threat of substitutes and the positioning of rivals – that affect the nature and degree of competition within an industry and that also shape the strategy of an individual organisation within that industry. This effect of the structure of a market on the conduct of an organisation – as further researched in the structure-conduct-performance paradigm (Porter, 1985) – is especially interesting when taking into account that the structures of markets are
changing due to information technology developments such as e-business (Wymbs, 2000). Consequently, it influences the effect of the five forces. In this section, the threat of new entrants, the threat of substitutes and the positioning of rivals will be discussed using the influence of the industry sector on e-business. The bargaining power of customers and suppliers will be discussed with the term supply chain.
2.4.1 Industry sector
consumer goods only one third of the companies make use of business-to-business e-commerce, while in the chemical industry and in financial services more then half of the organisations use e-business and in a sector like telecommunications this even amounts to two thirds (Bertschek & Fryges, 2002).
Windrum & De Berranger (2003) show that there are several characteristics of an industry sector which seem to influence the adoption rate of e-business within small and medium-sized enterprises. The research mentions the intensity of both knowledge and technology in a sector as an influence for the use of e-business. Furthermore, it notices that the industry life cycle has an effect the adoption rate of IT, with upcoming sectors having a higher rate than more mature industries. The usage of e-business is also affected by the structure of the supply chains in a specific sector. However, this last effect will be more thoroughly discussed in the next section.
Some researchers like Mamer & McCradle (1987) have found that competitors in substitute goods negatively influence each other’s probability of adoption innovation. That is, the more likely one organisation is to adopt a technology, the less likely its competitor is adopting this same technology. However, authors such as Windrum & De Berranger (2003) and Katz & Shapiro (1985) explain the bandwagon effects as stated in the introduction from the theory of network externalities. Their research shows that the larger the adoption rate of information or communication technology among competitors and customers, the more likely a firm is to also adopt such technology. For not only does the value of the network increase with the number of participants, the competitive advantage of the non-participants decreases as well. It is assumed that with regard to e-business the theory of network externalities will have a stronger effect than the theory of substitute competition, because the latter describes innovations in general and the former focuses on IT technologies in particular. These considerations lead to the following supposition:
organisation.
2.4.2 Supply chain
E-business is – together with other macro-economic forces as globalization and product life cycle shortening – seen as a major contributor to supply chain integration. It affects processes like procurement, distribution, and marketing and can greatly improve business indicators as efficiency, responsiveness, and time to market. Lee & Whang (2001) have identified four key dimensions on which this impact of e-business on the integration of supply chains occurs. The first dimension of information integration focuses on sharing all decision-influencing information, such as demand data, production and shipment schedules, and capacity and inventory levels, between supply chain partners in order to reduce the bullwhip effect. With planning synchronisation a supply chain can mutually agree on specific and coordinated actions by its members and with workflow
coordination it can decide in which way products and services are delivered and focuses on the critical business processes from first supplier to end customer. The final dimension is new business models which describes the potential of a well-integrated supply chain and the limitless business opportunities which can stem from it. However, these
improvements do not explain the effect of the structure of supply chain on the decision to implement e-business.
An important remark of Lee & Whang (2001) while investigating these four dimensions is the need for collaboration and cooperation. The research mentions the importance of monitoring and measuring the effort and performance of each party involved in the supply chain. Roles and responsibilities of partners must be clearly defined and
only for these most profitable customers, while it helps reduce costs for unprofitable customers in the bottom share. These top share customers, being small in number and important for profitability, individually can also be powerful enough to exert pressure. Therefore, it is assumed that these consumers could drive the decision to implement e-business. These considerations lead to the following supposition:
H5: The bargaining power of the customers of a small or medium-sized enterprise has a positive effect on the choice to implement e-business within that organisation.
2.5 Factors on a micro level
The influencing factors that ensue from the micro environment of a small or medium-sized enterprise will be investigated on a structural, a strategic and a tactical level. It should be noted that also operational issues could have an effect, but that its influence would be too hard to discover in this type of research. Therefore, in the following section respectively the size of the companies, the strategy of a single company and its operations will be researched.
2.5.1 Size
As small and medium-sized businesses are determined by the number of employees and financial indicators as turnover and balance sheet total, it is important to investigate if the indicators of this definition on themselves influence the success rate of e-business. To put it simpler, to research if time and money are truly enablers for e-business value or that it is just a matter of proportion. Levenburg (2005) investigated to which degree the size of an organisation influenced the type of e-business practices used. The article shows that the smaller the organisation, the more likely it was that e-business was used for market research purposes instead of communication with supply chain members. It also mentions that this supports earlier findings that smaller businesses use e-business for buying
More interestingly, the research (Levenburg, 2005) also focused on the performance of e-business usage among small and medium-sized enterprises using four indicators,
including mentioned improvement in profits and shipping costs. It concluded that there was no significant difference in performance between the smaller and larger companies. According to Levenburg (2005), there is a large section of small-sized organisations that do not recognize the benefits of e-business. It explains that very small companies may wrongly feel that the nature of their operations simply do not justify the costs associated with e-business. However, the research shows that within the different size-types better performing organisations were using more e-business practices than less performing organisations. These considerations lead to the following two suppositions:
H6a: The number of the employees in a small or medium-sized enterprise does not have a significant effect on the choice to implement e-business within that organisation. H6b: The annual turnover of a small or medium-sized enterprise does not have a significant effect on the choice to implement e-business within that organisation.
2.5.2 Strategy
As mentioned in the introduction of the meso environment, the strategy of an individual organisation is shaped by five competitive forces (Porter, 1979). That is, in order to be profitable within an industry, a company has to find a favourable position to gain a sustainable competitive advantage. According to Porter (1980), there are three generic ways to position an organisation – by cost leadership, by differentiation or by focus. With a cost leadership strategy a company tries to become the lowest-cost producer in the industry, with a differentiation strategy a company tries to be unique in its product, its marketing or its processes and with a focus strategy a company focuses on cost or
differentiation within a specific segment of an industry. Treacy & Wiersema (1993, 1995) categorise strategy into operational excellence, product leadership and customer intimacy, focusing respectively on the best total cost, the best product and the best total solution.
influences the industry structure – as earlier mentioned in the perspective of the meso environment (Wymbs, 2000) – and can provide opportunities for strategic positioning. Kamann (2002) shows how new roles were created due to the effect of e-business on traditional portfolio models – such as that of Kraljic (1983). The research presents the role of broker focusing on organising supply and demand, the role of capacity supplier focusing on production and the role of co-developer focusing on design. Kamann (2002) also mentions the importance of logistics and supply chain management as a bonding agent between these three roles. Thus, it is reasonable that Coltman et al. (2000) mentions that elements such as competitive advantage and strategies with regard to e-business play an important role during the second wave of e-business. After the critical positions had been taken during the first wave of e-business and the land grab on the internet, it became essential in defending those positions and attacking positions of competitors.
Evans & Wurster (1999) explain this strategising of e-business, which they call
navigation, further by giving three dimensions on which organisations can compete. The first dimension, reach, focuses on accessibility. This is measured by the ease for
customer to the organisation, even more so when such customers are willing to pay for the quality such organisations offer.
The most important conclusion in the research of Evans & Wurster (1999) is that different types of organisations because of their inherited limitations have to focus on a certain set of dimensions and how to behave within the dimensions themselves. For instance, retailers will need another approach towards the three dimensions than product manufacturers in order to become successful in e-business. These considerations lead to the following supposition:
H7: The balanced mix of reach, richness and affiliation for a specific e-business strategy within a small or medium-sized enterprise has a positive effect on the choice to
implement e-business within that organisation.
2.5.3 Operations
The operations of an organisation are of all the factors mentioned the most intertwined with e-business. Not only do the current operations affect the probability of the success of e-business, reversibly can the introduction of e-business change the way an organisation does business in almost a natural and complete manner. Boyer (2001) has investigated the opportunities and threats of e-operations and thereby possibly gives a good insight into the opposite effect of operations on e-business. The article looks into four benefits and four drawbacks of introducing e-business with regard to the operations of an
organisation.
First of all, the research mentions the positive cost effects that arise from the possibility of centralisation. Organisations with e-business could choose to reduce the number of locations near the end customer. Thus, these organisations can save costs on the use of facilities and the amount of inventory held. A side effect from this centralised
organisation is the ability to specialise jobs and to make simpler schedules. Such
can occur when customers are encouraged to relief the company of some basic tasks. This self-sourcing is a fourth benefit of e-business and ensues from the value customers
experience in doing business online and in exchange deliver accessible information of their purchase.
On the other hand, centralisation can lead to a kind of alienation from the consumer. The article of Boyer (2001) shows that communication becomes less flexible due to less face-to-face interaction and effective e-business heavily depends on the internal translation and integration with existing systems. Also, an increase in the physical distance from the customer will lead to higher shipping costs and an increase in the uncertainty in lead time. Furthermore, as already discussed in the section on the macro-environmental influences, technology will form an important factor in the organisation. For instance, the dependability on the functioning of the system increases dramatically and there will be a quite large need for sufficient tech-skilled employees. Lastly, the organisation may have to deal with changes in accountability and legality. Issues with verification and security of transactions can form a barrier to the introduction of e-business.
H8: The expected improvement of operational scalability in a small or medium-sized enterprise by e-business has a positive effect on the choice to implement e-business within that organisation.
2.5.4 IT infrastructure
The sections on operations and development in IT already introduced how important the role of technology in the success of e-business can be. For example, the e-operations measurement tool of scalability includes the intensity of information. However, with the use of net effects, the dependability on information technology can be underestimated within this tool. Zhu (2004) explains that the value of IT infrastructure has been ignored and researched this problem from a resourced-based view. This theory explains that the resources of an organisation can give it a competitive advantage (Grant, 1991). With regard to this specific information technology, Zhu (2004) has found strong synergy effects between back-end IT infrastructure and the capabilities of front-end e-business.
Weill & Vitale (2002) have investigated the building blocks of several forms of e-business and examined the specific need for IT infrastructure of each initiative. According to this research, the infrastructure with regard to information technology consists of four components. These are technological components such as hardware and operating systems, human infrastructure such as knowledge, skills and experience, shared services such as data management and security, and shared and standard applications such as accounting and budgeting. The capability of this infrastructure is the reliable integration of these four components in order to support new and existing IT initiatives. A very capable infrastructure can greatly reduce the time and costs of an implementation.
approach with regard to the IT infrastructure and different investment choices. Thus, a small or medium-sized enterprise would need an IT infrastructure that is capable enough to introduce the e-business approach most suitable for their situation. These
considerations lead to the following supposition:
H9: The adequate capability of the IT infrastructure for a specific e-business approach within a small or medium-sized enterprise has a positive effect on the choice to
implement e-business within that organisation.
2.6 Conceptual model
The previous sections investigate the influences on a macro, meso en micro level – as mentioned by Fillis, Johannson & Wagner (2004) – on the third stage of the adoption model as researched by Rogers (1983) and Nooteboom (1994), namely decision, with regard to implementing e-business. This section will summarise suppositions as stated above and explain the conceptual model as seen in figure 4. Furthermore, it will explain and operationalise the variables within that model. The conceptual model shows that the most important variables are the dependent variable decision and the two mediating variables risk and value. Therefore, the sections below will primarily discuss these three variables, while explaining the independent variables within that discussion.
2.6.1 Decision
The decision is the choice for introducing e-business in a small or medium-sized business after a consideration between the risks and the opportunities involved with this
decision-making process as researched by Eisenhardt & Zbaracki (1992) will not be taken into account in this research. Therefore, the first sub question of this research will be the following:
Does the positive effect of the value of e-business outweigh the negative effect of the risk of e-business in order to provide leverage for small and medium-sized enterprises to decide to implement e-business?
FIGURE 4: Conceptual model
It is expected that the bargaining power of the companies’ customers will have a positive effect on the decision. That is, the lower the number of clients responsible for the vast majority of the turnover of a small or medium-sized company, the higher the bargaining power of these individual customers and also, the more interested these customers are in using e-business, the more eager the company will be to implement this technology. The adoption rate of a companies’ substitute competitors is also expected to have a positive effect on the decision. That is, the more direct competitors have adopted e-business, the more likely a smaller business will choose for e-business. The size of a company – measured by the number of employees and the annual turnover of the enterprise – is seen
as a control variable. Therefore, the second and third sub questions of this research will be the following:
Do the positive effects of the bargaining power of customers and the adoption rate of e-business by substitute competitors provide leverage for small and medium-sized enterprises to decide to implement e-business?
Does the size of a company provide a barrier or leverage for small and medium-sized enterprises to decide to implement e-business?
2.6.2 Value
Value is the expected improvement in both operational excellence and financial consumer measures. This means to lower operational costs and to increase profitability. It is
expected that the awareness by the owner of the company to introduce a specific mix of reach, richness and affiliation with regard to its e-business strategy will have a positive effect on the value of e-business. Thus, a formulated strategy specific for e-business activities with a focus on accessibility, detailed information and/or customer interest could open up more opportunities to increase revenues. Scalability also is expected to have a positive effect on value. The operationalisation of advantages and disadvantages of each e-business approach could be important in finding the most suitable type. For, the less constrained an e-business approach in terms of complexity and need for support is, the more value it will yield for the organisation. Furthermore, the awareness with regard to the supportive role of e-business in eco-friendliness is expected to have a positive effect on value. It could help companies to become more sustainable by increasing their efficiency and thus increasing the value e-business can deliver. Therefore, the fourth sub question of this research will be the following:
2.6.3 Risk
Risk is essentially all the costs involved with the introduction of e-business in an organisation. It is expected that the perceived incertitude with regard to the economic developments will have a positive effect on the risk of implementing e-business. That is, the higher the uncertainty concerning the growth prospects, the greater the financial risk for the organisation to implement a new technology such as e-business. The capability of the IT infrastructure is expected to have a negative effect on risk. If an organisation has a IT infrastructure that is capable enough to support the implementation of a specific e-business approach, the prospective time and costs surrounding the implementation of this approach will be lower. Furthermore, government initiatives in the form of subsidies are expected to have a negative effect on risk. The use of available subsidies can lower the total costs of implementing e-business in an small or medium-sized enterprise. Therefore, the fifth and sixth sub question of this research will be the following:
Do the possibilities for governmental subsidies and adequate capability of the IT infrastructure have a negative effect on the risk of implementing e-business?
3. DATA ANALYSIS
This section will discuss the analysis of the data received from an online survey on the variables and relationships in the conceptual model. First, the paper will focus on the process of collecting data by explaining the methods of acquiring and processing the data in such a way that the relationships within the conceptual model could be tested properly. All the steps that were necessary to receive the appropriate data and to configure these into useful figures will be looked into. Second, it will discuss the manner of analysing the data and the factual results that originated from this analysis. That is, to explain the way the processed data from the survey was analysed and to show the figures of all significant correlations gained in this analysis.
3.1 Data acquirement and processing
In order to acquire the data needed to test the relationships within the conceptual model in a proper manner, three key processes – structuring of data collection, selection of suitable companies and contacting respondents – were executed. Furthermore, in order to analyse the collected data, it was processed accordingly. The structuring process focused on constructing a survey in which the elements of the conceptual model were discussed and the selection process focused on obtaining an appropriate set of respondents. The contact process focused on approaching the selected companies and the process of data handling and processing focused on receiving and recoding the data. These processes will be discussed more extensively below.
Companies that made use of e-business were asked on their experience with regard to the decision making process, while companies that did not were asked on their opinion as if they would have to make that decision. Furthermore, a few factual questions on elements such as size, customers and direct competition with categorized multiple-choice answers were formulated. Lastly, one question with multiple answers possible focused on which type of e-business the companies used or considered to use. The respondents had to answer nine or ten main questions in total depending on their specific section. The questionnaire which was written in Dutch and sent to the selected business can be found in Appendix I.
The process of selection followed two steps in order to select a manageable amount of companies in accordance to definition of the research population. Firstly, the process used the first three limitations of the research population, namely size, location and industry sector to select appropriate companies from the database of Review & Analysis of Companies in Holland (REACH) by Bureau van Dijk. This company information and business intelligence database contains data of more than 2 million active companies and over 7500 active branches in The Netherlands. From this first step 2,436 companies were selected. This was roughly 40% of the total number of small and medium-sized business locations located in the North-Netherlands focused on manufacturing, namely 6,155 as earlier stated. Secondly, the process used mainly the fourth and fifth limitation of the research population – supply chain role and consumer value – to reduce the number of selected companies by hand to 226 companies or about 9%. In this process the
classification system of economic activity known as Standaard Bedrijfsindeling (SBI) played a key role.
Contacting the respondents was a two-fold effort in trying to convince the selected
promising towards e-business. These companies were chosen based on available online information and were approached by telephone to friendly remind them of the letter and to repeat the request of participation.
The data handling and processing focused on receiving the data and recoding it for analysis. For the survey was made electronically available, data could easily be accessed and stored. The data was stored in several types of databases, namely comma-separated values, SPSS save files and rich text files of the relative and absolute values of the answers. The data in these databases were mainly plain text and had to be organised and recoded in order to be analysed. For example, the allocation of data type mostly had to be reset to the ordinal level and the answers to questions in negative form had to be switched in order to give a correct representation of the relationships.
3.2 Data analysis
The received and processed data were analysed for significant correlations between the variables. This section will look into the technical part of this analysis only. This means that it will focus purely on the numerical side of the data received from the survey. The interpretation of this analysis will be discussed separately in a later stage. Therefore, this section will show the figures of the variables, both on themselves as in relation to each other. However, before going into the separate analysis of each variable, the method of analysis will be discussed.
3.2.1 Method of analysis
In total, eighteen of the 226 contacted businesses returned a complete or almost complete questionnaire. The few missing values were not to such an extent that they gave a reason to remove one of the respondents from the analysis. Within these eighteen, there were seven (39%) companies that have already implemented e-business – from now on called e-business companies – and there were eleven (61%) companies that did not – from now on called non-e-business companies. As stated earlier, the data were recoded in SPSS and subsequently analysed on the correlation between certain values using both the
coefficient (Kendall's tau-b). The linked values were based on the relationships as presented in the conceptual model and were for the most part split into analysis for the different sections in the survey. In order to avoid the risk of multicollinearity of certain values – due to the number of variables in respect to the number of respondents – likewise variables were combined or removed. The remaining available data did not support any further advanced analysis. The level of significance for this two-tailed
analysis was determined at 95%. The difference in significance of the correlation between the two analyses of the correlation coefficient will be treated accordingly. The significant correlations for each variable in the conceptual model will be discussed further below, using the analysis from both coefficient tests as well as the relative values on the separate Likert-items.
3.2.2 Influences on decision
This section will discuss the influences on the main dependent variable from the conceptual model, namely decision. According to the model, its most important influences are expected to be the mediating variables of value and risk. These two variables and the influences on themselves will be also discussed more thorough in later sections. Furthermore, the decision is expected to be influenced positively by the
bargaining power of consumers and by substitute competitors. Lastly, the factor of size will be discussed as it is seen as a control variable. Thus, it will discuss the first, second and third sub question of this research.
3.2.2.1 Influence of value and risk
The decision to implement e-business within a company is split amongst the two
A large majority of both groups (80%) agrees that the value of e-business is of
importance when making the decision to implement it or not. However, only half of the respondents thinks that e-business has created or will create a lot of value for the organisation. The risk involved with implementing e-business does divide the groups. The e-business companies are undecided with regard to both the amount of risk and the importance of risk, while 70% of non-e-business companies agrees that risk is of importance when implementing e-business. Analysis – as presented in table 2 – shows that there is a strong negative significant correlation (0.7; p=.01) between the risk of implementing e-business and the willingness of the non-e-business companies to choice to implement e-business at this time.
TABLE 2: Correlation analysis decision I
E-business
Value Risk Decision
Rho Tau-b Rho Tau-b Rho Tau-b
Value Corr.Sig. 1 1
. .
Risk Corr.Sig. -,54,21 -,51,19 1. 1.
Decision Corr. -,34 -,33 ,32 ,27 1 1
Sig. ,45 ,40 ,49 ,47 . .
Non-e-business
Value Risk Decision
Rho Tau-b Rho Tau-b Rho Rho
Value Corr.Sig. 1 1
. .
Risk Corr. -,13 -,12 1 1
Sig. ,72 ,69 . .
Decision Corr. ,00 ,00 -,74** -,67* 1 1
Sig. 1,00 1,00 ,01 ,02 . . **. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
3.2.2.2 Influence of bargaining power and substitute competitors
companies. An overview of these figures can be found in table 3. For most companies (in both groups about 40% or 50%) the vast majority of turnover is acquired from between 20% and 40% of the consumers. The other half of companies is quite evenly distributed over the remaining categories. However, only one-third of the e-business and non-e-business companies has acknowledged to have ever received any interest with regard to implementing e-business by a part of these most-important consumers.
TABLE 3: Number of regular customers per company
Number of regular customers Number of companies
1 - 49 customers 1 company 50 - 249 customers 6 companies 250 - 499 customers 4 companies 500+ customers 7 companies
According to the survey, the substitute competitors of both e-business companies and non-e-business companies are rated quite equally technologically advanced. Roughly half of the companies thinks that at least twenty percent of its direct competitors is
technologically advanced. However, in at least 70% of the e-business companies some of the substitute competitors had implemented e-business, while in 60% of the
TABLE 4: Correlation analysis decision II
E-business
Barg. power Subst. comp. Decision
Rho Tau-b Rho Tau-b Rho Tau-b
Barg. power Corr.Sig. 1. 1.
Subst. comp. Corr. ,34 ,31 1 1
Sig. ,51 ,41 . .
Decision Corr. -,60 -,53 ,28 ,29 1 1
Sig. ,21 ,17 ,58 ,47 . .
Non-e-business
Barg. power Subst. comp. Decision
Rho Tau-b Rho Tau-b Rho Rho
Barg. power Corr.Sig. 1. 1.
Subst. comp. Corr. ,51 ,46 1 1
Sig. ,13 ,11 . .
Decision Corr. ,25 ,20 ,85** ,79* 1 1
Sig. ,46 ,44 ,00 ,01 . .
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
3.2.2.3 Influence of size
TABLE 5: Correlation analysis decision III E-business Number employees Annual turnover Decision
Rho Tau-b Rho Tau-b Rho Tau-b
Number employees Corr. 1 1 Sig. . . Annual turnover Corr. ,78** ,75** 1 1 Sig. ,00 ,00 . . Decision Corr. -,26 -,21 ,17 ,14 1 1 Sig. ,58 ,58 ,72 ,70 . . Non-e-business Number
employees turnoverAnnual Decision
Rho Tau-b Rho Tau-b Rho Rho
Number employees Corr. 1 1 Sig. . . Annual turnover Corr. ,78** ,75** 1 1 Sig. ,00 ,00 . . Decision Corr. -,58 -,55 -,41 -,39 1 1 Sig. ,06 ,06 ,32 ,25 . .
**. Correlation is significant at the 0.01 level (2-tailed).
3.2.3 Influences on value
This section will analyse the proposed influences on value as stated in the conceptual model. This showed that there were three variables expected to affect the value of business, all of them in a positive manner. Those variables were a specific mix of e-business strategy, the scalability of the e-e-business approach and awareness to the positive role of e-business in eco-friendliness. Thus, it will discuss the fourth sub question of this research.
3.2.3.1 Influence of strategy
Roughly half of the non-e-business companies indicate that they intend to strategize their e-business implementation, while only a third of the e-business companies has formulated such specific strategy. On the other hand, more than 60% of the non-e-business
Furthermore, almost all companies think that a strategy for e-business should focus on the accessibility of products and about a half also thinks that strategy should focus on
customer contact. The analysis – as presented in table 6 - shows that there is a weak positive significant correlation (0.8; p=.05) between formulating a strategy and the value of e-business implementation for e-business companies. Furthermore, there is a positive significant correlation (0.7; p<.05) between formulating a strategy and the value of e-business implementation for non-e-e-business companies.
TABLE 6: Correlation analysis value I
E-business
Strategy Eco-impact Value
Rho Tau-b Rho Tau-b Rho Tau-b
Strategy Corr.Sig. 1. 1.
Eco-impact Corr. -,19 -,08 1 1
Sig. ,72 ,83 . .
Value Corr. ,85* ,78 ,82* ,78* 1 1
Sig. ,03 ,06 ,03 ,04 . .
Non-e-business
Strategy Eco-impact Value
Rho Tau-b Rho Tau-b Rho Rho
Strategy Corr.Sig. 1 1
. .
Eco-impact Corr. ,87** ,84** 1 1
Sig. ,00 ,00 . .
Value Corr. ,72* ,69* ,81** ,79** 1 1
Sig. ,02 ,02 ,00 ,01 . .
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
3.2.3.2 Influence of awareness eco-impact
The companies are mildly positive with regard to their efforts in environmental
