Factors influencing e-commerce implementation: analysis of survey results.

ABSTRACT

Despite the evident increase in importance of e-commerce and effectiveness of its implementation, until recently little research has been undertaken to investigate the factors that influence the results of implementing e-commerce solutions. This paper presents a general assessment of e-commerce implementation results and analysis of factors that influence these results. The analyzed factors include: company size, comprehensiveness of implemented e-commerce solutions and specific solutions (sell-side, buy-side, exchanges and auctions). Through hypothesis testing we identified relationships between these factors and e-commerce implementation results (revenue growth and cost reduction). It was proven that a larger company size and comprehensiveness of e-commerce solutions positively influence e-commerce implementation results. Conversely, a small company size may negatively influence these results. Also, we concluded that sell-side e-commerce solutions improve revenue growth, whereas buy-side solutions reduce costs. At the same time, we identified that e-commerce exchanges/auctions did not have significant influence on implementation results.

1. INTRODUCTION

E-commerce is becoming a major element of competitive advantage in the modern business environment. Survey after survey conducted by a variety of companies (Gartner, 2003, Forrester/ISM, 2003, eMarketer, 2003) indicated an accelerating volume of transactions in business-to-consumer (B2C) and particularly in business-to-business (B2B) e-commerce. For example, eMarketer (2003) predicted that global B2B e-commerce revenues would grow to $1.41 trillion in 2003, with the United States accounting for half of the total. Worldwide B2B e-commerce revenues will reach $2.37 trillion in 2004 (eMarketer, 2003).

Although B2B sales continue to dwarf B2C sales, many retailers now see online sales as their best outlet for new growth. According to Forrester Research (2003), online retail sales in the United States are expected to hit $96 billion in 2003, which is around 25% of increase from the previous year. Forrester also predicted that U.S. e-commerce will grow at a 19% rate over the next five years, fueled by a steady stream of new online shoppers and new product category sales. Online retail will reach nearly $230 billion and account for 10% of total U.S. retail sales by 2008. The projected e-commerce growth raises the interest of researchers to understand how effective and efficient this e-commerce implementation has been and what influences e-commerce implementation results in manufacturing and service organizations. A number of surveys have been reported that examine the implementation of e-commerce solutions. These surveys are based on evaluating a specific industry, i.e., manufacturing, construction, services, etc. (Rae, 2003), or they are concerned with various groups of e-commerce solutions such as sell-side storefronts, buy-side e-procurement, electronic exchanges, auctions and others (ISM/Forrester, 2003; Garnter, 2002; eMarketer 2003).

A Forrester/ISM survey (Kioa and Mirphy, 2003) examined implementation of buy-side e-commerce solutions, i.e., reverse auction and e-procurement with catalogs, in both manufacturing and service organizations. The survey described a variety of implementation results associated with a proportion of companies using buy-side e-commerce solutions; volume of transactions; implementation results in terms of cost reduction; and perspectives on using buy-side e-commerce solutions. One interesting conclusion presented in the Forrester/ISM survey was that large corporations have had a higher rate of successful implementation of e-commerce solutions than that of small companies. However, the analysis of the survey results did not go further to present other factors that may influence e-commerce implementation results.

Desisto and Sarner (2003) from Gartner, Inc. have done a similar analysis of sell-side (store) e-commerce solutions. The survey results were associated with the growth of sell-side e-commerce, specifically B2C e-tailing; percentage of growth in different product categories, internal (with employees) and external (with customers) efficiency of implementing e-commerce solutions. However, this survey did not analyze what influenced implementation of sell-side e-commerce solutions in various organizations.

Despite the evident increase in importance of e-commerce and effectiveness of its implementation, until recently little research has been undertaken to investigate the factors that influence the results of implementing e-commerce solutions. Such a knowledge not only has potential benefits for organizations considering e-commerce implementation but also for those organizations that have already engaged in such implementations, because it can provide them with an understanding of how to facilitate and improve their implementation process.

Recent work by Begin and Boisvert (2003) analyzed strategic factors that influence e-commerce implementation. They have divided these factors into two main groups: organizational and individual. The organizational factors include: culture, structure and systems, technology, and expertise. The individual factors were associated with perception, training and competences, and leadership. This classification could serve as a good starting point to analyze these factors and identify their influence on e-commerce implementation results. However, this analysis has not been done in the paper.

Another paper by Wilkins et al (2001) has looked at the impact of e-commerce implementation by government agencies on user organizations, with particular emphasis on the social and organizational contexts in which such e-commerce implementations take place. This body of work offers some insight into the issues surrounding the adoption of various e-commerce solutions, but does not focus on providing understanding of actual factors that could positively influence e-commerce implementation results. We believe that understanding of these factors may offer a significant insight into how companies should approach e-commerce implementation.

Some researchers have focused on investigating factors leading to the success of B2C e-commerce (Kendall & Kendall, 2001; Wu, 2003; Govindarajulu at al, 2004). These factors reflect specific e-commerce solutions being implemented, their interrelationship, and organizational support (management commitment, employee awareness, etc.). The authors have admitted that combination of several e-commerce solutions (their interrelationship) can produce better results than separately implemented e-commerce solutions. However, they did not provide any quantitative analysis that established relationship between these factors and e-commerce implementation results.

The analysis of popular e-commerce textbooks (Turban at al, 2004; Rayport and Jarovski, 2001; Laudon and Traver, 2003; Eisenmann, 2002) also confirmed our previous conclusion that little has been done to quantitatively explain the influence of various business factors on e-commerce implementation. For example, Turban at al (2004) described strategic elements of developing successful e-commerce solutions including: e-business planning and funding; building the web site; web site hosting; content creation and management; web site design, construction, and promotion; and customer relationship management. However, these materials would not specify and explain factors that facilitate (influence) e-commerce implementation results.

Overall, the evaluation of literature sources clearly demonstrated a need to develop the research agenda on establishing and analyzing factors that influence implementation of e-commerce solutions in various organizations. This agenda would be associated with a general assessment of e-commerce implementation results and identification of quantitative and qualitative factors that may influence these results. In this research, we addressed the specified issues of establishing and analyzing such factors. Details of the research methodology and results of our study are presented in the following sections of this paper.

2. METHODOLOGY

The objectives of this research were to (1) understand how efficient e-commerce implementation results have been and (2) what influenced these implementation results. To fulfill the research objectives, we have established a set of the following research questions that we intended to answer:

* Have implementation of e-commerce been successful in organizations?

* What are measurements that can be used to assess e-commerce implementation results?

* Does the company size influence results of e-commerce implementation?

* Does the number/comprehensiveness of solutions influence implementation results?

* What solutions are the more efficient in terms of e-commerce implementation results?

The main research steps and their outcomes are presented in Figure 1.

[FIGURE 1 OMITTED]

To address the research objectives and associated research questions, we have conducted a survey involving companies in the San Francisco Ray Area. These companies varied in terms of industry, size, and products/services. The manufacturing companies participated in the survey were from electronics, computer, telecommunications equipment, automotive, and other technology-rich industries. The service companies responded in the survey were even more diversified including large-chain grocery stores, computer services, retail stores, software development services, and some others.

We have gotten back and analyzed 31 completed surveys from those companies. The survey questionnaire consisted of 17 questions that required respondents to provide the following information on e-commerce implementation:

* Groups of e-commerce solutions (storefronts, reverse auctions, catalog e-procurement, exchanges, forward auctions, etc.) that were implemented in organizations and the number of these solutions

* Quantitative and qualitative indicators used to measure the overall results of implementing e-commerce solutions

* Cost categories that have been affected by e-commerce implementation

* Main benefits of implementing e-commerce solutions

* Main drawbacks of these implementations.

Also, a number of questions in the survey required to rate e-commerce implementation results based on a 5-point scale in terms of:

* Overall rates of design and capabilities of e-commerce solutions in organizations

* Overall rates of business results due to e-commerce implementation

* Rates of the influence that the implemented e-commerce solutions had on revenues, costs, order-to-fulfillment and procure-to-pay times.

To address factors influencing e-commerce implementation results, we have established the following hypotheses that we intended to test utilizing the survey results:

* Hypothesis 1: Company size influences e-commerce implementation results.

* Hypothesis 2: Comprehensiveness of the implemented e-commerce solutions positively influences (improves) implementation results.

* Hypothesis 3: Sell-side e-commerce solutions increase revenue.

* Hypothesis 4: Buy-side e-commerce solutions reduce cost.

* Hypothesis 5: E-commerce exchange/auction solutions increase revenue and reduce cost.

The survey results and associated hypotheses testing have been presented in the following sections of this paper.

3. GENERAL SURVEY RESULTS

The results of the survey showed an overall successful implementation of e-commerce solutions in organizations. More than 61% of respondents (see Table 1) stated that implemented e-commerce solutions increased or significantly increased revenues. At the same time, 58% of those responded achieved decrease or significant decrease of costs through the implementation of e-commerce solutions.

According to the survey results, the most important cost categories that were reduced appeared to be: transactional cost specifically in terms of paperless transactions, administrative cost associated with reduction of purchasing procurement personnel, inventory cost, and reduction of prices of materials and services. All this represents typical cost savings results associated with e-commerce implementation.

At the same time, the implementation of e-commerce solutions was also successful in terms of reducing order-to-fulfillment time as well as procure-to-pay time. 48% and 58% of respondents, respectively, considered those times to be reduced or significantly reduced due to e-commerce implementation. Overall, the survey results indicate that implementation of e-commerce solutions have been successful in various manufacturing and service organizations. In fact, the above results are similar to those discussed in the Introduction section of this paper (eMarketer, 2003, Gartner, 2003, Forrester, 2003).

When asked about the main benefits of implementing e-commerce solutions, the respondents have presented relatively evenly distributed answers, which are shown in Table 2.

However, responses on the question of drawbacks and problems in implementing e-commerce solutions demonstrated that the three most critical problems in e-commerce implementation were high costs of implementation, data security, and low liquidity (not enough buyers and sellers), which covered more than 2/3 of responses (see Table 3).

According to the survey results, the most common e-commerce solutions were online sell-side (online storefronts) that were implemented in more than 1/3 of all organizations (see Table 4).

The results presented in Table 4 were not surprising or out of range. Sell-side e-commerce (storefronts) is the most common type of e-commerce solutions in the market today. Buy-side e-commerce solutions (reverse auctions and e-procurement with catalogs) are the next most common implemented solutions. However, the companies have had very low response on utilization of forward auctions and public exchanges (2.7% and 8.1% of respondents, respectively). These results were in lieu of a general trend that showed a continuous decline of the number of implemented public exchanges and forward auctions. One of the survey questions inquired about the quantitative and/or qualitative measurements (indicators) used to measure the overall results of implementing e-commerce solutions. The survey results did not produce a single leading indicator from these measurements (see Table 5).

As can be seen from table 5, the most common indicators of e-commerce implementation are: cost reduction due to e-commerce solutions, revenue growth generated through online sales, return on investments, improved customer satisfaction, profit growth generated through online sales, decrease in procurement/purchasing cycle time, and decrease in delivery time. The responses for the specified indicators varied from the maximum of 15% for cost reduction to about 11% for decrease in delivery time. This did not show a clear pattern in terms of using specific indicators. However, the usage of these indicators may directly depend on implemented solutions (storefronts, reverse auctions, procurement, etc.).

For the purposes of analyzing factors that influence e-commerce implementation results, we utilize the first two (most frequently used) measurements, i.e., cost reduction and revenue growth.

4. FACTORS INFLUENCING IMPLEMENTATION OF E-COMMERCE SOLUTIONS

The survey data enabled to test the hypotheses presented in the Methodology section in order to understand what factors influence results of e-commerce implementation. These factors were associated with company size, comprehensiveness of implemented solutions, and specific e-commerce solutions.

According to the survey, companies, depending on their size, were grouped into three main categories: small companies (less than $100Mln in revenues), mid-size companies ($100Mln-$1Bln), and large companies (above $1Bln). According to the survey, almost 20% of companies were of small size, 38% were mid-size companies, and almost 42% were large companies.

Comprehensiveness of implemented solutions was defined as a number of solutions that has been implemented in each surveyed company (see Table 4). Around 19% of the surveyed companies implemented 4 or more e-commerce solutions; almost 23% of these companies implemented 3 solutions; 42% of surveyed companies introduced 2 solutions; and 16%--only one solution. As can be seen from this data, the most popular scenario was a company with either two or three implemented e-commerce solutions.

The specific solutions considered for analysis are presented in Table 4. According to the hypotheses described in the Methodology section of the paper, we intended to identify efficiency of sell-side (storefront) solutions, buy-side solutions (reverse auctions and e-procurement with catalogs), electronic exchanges (private and public) and forward auctions.

To analyze influence of the described factors on e-commerce implementation results, we considered these results in association with their assessment by the surveyed companies (see Table 1). The analysis was concerned with identifying relationships between the described factors (company size, comprehensiveness, and specific solutions) and both revenue growth and cost reduction in these companies. For that, we have identified, utilizing the SPSS software, correlation coefficients between the factors and e-commerce implementation results. The correlation coefficients between the e-commerce implementation results (revenue growth and cost reduction) and two factors (company size and comprehensiveness of e-commerce solutions) are presented in Table 6.

As can be seen from table 6, there is a statistically significant positive correlation (p < 0.05) between the large and mid-size company size and e-commerce implementation results in terms of revenue growth and cost reduction. With small companies, the correlation analysis also showed a statistically significant correlation with implementation results but with a negative sign. This means that a small size of the company may adversely affect e-commerce implementation results in this company. Overall, we need to accept Hypothesis 1 described in the Methodology section of the paper that company size does influence e-commerce implementation results. In fact, the correlation analysis clearly demonstrates that a company size may positively (in case of large and mid-size companies) or negatively (in case of small companies) influence the implementation of e-commerce solutions.

The results in Table 6 clearly demonstrate that comprehensiveness of e-commerce solutions positively affect e-commerce implementation results in terms of revenue growth and cost reduction. Thus, we would need to accept Hypothesis 2 that comprehensiveness of the implemented e-commerce solutions positively influences (improves) implementation results. The correlation coefficients between implementation results and various e-commerce solutions are presented in Table 7.

The data in table 7 shows that implementation of sell-side storefronts, reverse auctions, and e-procurement with catalogs has statistically significant positive correlation with the e-commerce implementation results, i.e., revenue growth and cost reduction. The p-value for the correlation coefficient between sell-side storefront and revenue growth is slightly higher than 0.05. However, we would still consider this relationship as statistically significant. Therefore, we need accept Hypotheses 3 that sell-side (storefront) e-commerce solutions increase revenue. We also need to accept Hypothesis 4, which is stated that buy-side e-commerce solutions (reverse auction and catalog e-procurement) reduce cost. It is important to point out that the value of correlation coefficients between sell-side (storefronts) and implementation results is not the highest among the analyzed e-commerce solutions. In fact, the highest values of correlation coefficient, 0.61 and 0.58 for revenue growth and cost reduction, respectively, belong to reverse auction, which is considered by some sources as the most cost-efficient e-commerce solution.

The results in Table 7 also demonstrate that implementation of public and private exchanges as well as forward auctions did not have statistically significant relationship with the e-commerce implementation results. Thus, we have to reject Hypothesis 5, which stated that e-commerce exchange/auction solutions increase revenue and reduce cost. However, it needs to be noted here that the last negative results may be partially due to a fact that exchanges and auctions were not well represented in a survey sample of companies (see Table 4).

5. CONCLUSION

The described in this paper analysis of literature sources and survey results has proven a need to develop and evaluate factors that influence implementation of e-commerce solutions in various organizations. Based on a general assessment of e-commerce implementation results, we were able to identify and quantitatively explain factors that may influence e-commerce implementation results. These factors were associated with company size, comprehensiveness of e-commerce solutions (number of solutions that have been implemented); and specific e-commerce solutions (sell-side, buy-side and exchanges/auctions). Based on the survey results and the established factors, we have introduced five research hypotheses that were tested using correlation analysis. The testing results are presented in table 8.

The correlation analysis of the survey data proved that the e-commerce implementation results are influenced by the company size. The larger the company size the more efficient the implementation results. At the same time, a small company size may adversely affect the e-commerce implementation results. Also, we found that comprehensiveness of the implemented e-commerce solutions can improve implementation results in terms of revenue growth and cost reduction. The sell-side (storefronts) and buy-side (reverse auctions and e-procurement with catalogs) e-commerce solutions appeared to positively influence (improve) revenue growth and cost reduction in organizations, respectively. However, we were not able to prove the existence of significant relationships between implementation of exchanges/auctions and e-commerce implementation results. This may be partially due to a fact that exchanges and auctions were not well represented in a survey sample of companies.

Overall, identification of the factors that influence e-commerce implementation results is not only important for practitioners, but also offers a significant insight on how companies should approach e-commerce implementation. The results received in this paper have potential benefits for organizations considering e-commerce implementation. Also, they are important for those organizations that have already engaged in e-commerce implementation, because it can provide them with an understanding of how to facilitate and improve their e-commerce implementation process.

TABLE 1: OVERALL RESULTS OF IMPLEMENTING E-COMMERCE

How was revenue affected by the implemented     Number of
e-commerce solutions                          responses (%)

Significantly increase                            16.1%
Increase                                          45.2%
No change                                          23%
Decrease                                           16%
Significantly decrease                             0%

How was cost affected by the implemented        Number of
e-commerce solutions                          responses (%)

Significantly decrease                            25.8%
Decrease                                          32.3%
No change                                          23%
Increase                                           19%
Significantly increase                             0%

TABLE 2: BENEFITS OF IMPLEMENTING E-COMMERCE SOLUTIONS

Main benefits of implementing e-commerce solutions in      Number of
organizations                                            responses (%)

Shorter procurement cycle                                        13.3%
Improve communication and relationships with suppliers           13.3%
Improve communication and relationships with customers           12.6%
Better reliability and control of purchase orders                11.9%
Better reliability and control of customer orders                11.9%
New channel of marketing and sale with global outreach           10.4%
Reduce inventory level and cost                                   8.9%
Eliminate or reduce the number of middlemen                       8.9%
Reduce purchase prices                                            7.4%

TABLE 3: DRAWBACKS AND PROBLEMS IN E-COMMERCE IMPLEMENTATION

Main drawbacks and problems in implementing              Number of
e-commerce solutions in organizations                  responses (%)

High costs of implementing e-commerce solutions                26.7%
Data security                                                  26.7%
Not enough buyers and/or sellers online                        13.3%
Poor integration with internal "back-office" systems            8.9%
Low return on investment and/or long payback period             6.7%
Not enough seed of connection/bandwidth problems                6.7%

TABLE 4: IMPLEMENTED E-COMMERCE SOLUTIONS

                                     Number of
E-commerce solutions               responses, (%)

Online store (storefront)                   33.8%
Reverse auction (online bidding)            16.2%
E-procurement with catalogs                 25.7%
Public exchange                              4.1%
Private exchange                             8.1%
Forward auction                              2.7%
Others (specify)                             9.5%

TABLE 5: MAIN INDICATORS OF E-COMMERCE IMPLEMENTATION RESULTS

Quantitative and/or qualitative indicators used to     Number of
measure the e-commerce implementation results        responses, (%)

Cost reduction due to e-commerce solutions                    15.0%
Revenue growth generated through online sales                 14.3%
Return on investments                                         13.6%
Improved customer satisfaction                                13.6%
Profit growth generated through online sales                  12.2%
Decrease in procurement/purchasing cycle time                 11.6%
Decrease in delivery time                                     10.9%

TABLE 6: CORRELATION RESULTS WITH COMPANY SIZE AND COMPREHENSIVENESS

                       Correlation              Correlation
                       with revenue              with cost
Factor                    growth      P-value    reduction    P-value

Company size
  Small                   -0.49        0.035       -0.45       0.038
  Mid-size                 0.45        0.038        0.44       0.038
  Large                    0.63        0.020        0.59       0.021

Comprehensiveness of
e-commerce solutions       0.73        0.015        0.68       0.018

TABLE 7: CORRELATION RESULTS: VARIOUS E-COMMERCE SOLUTIONS

                              Correlation with
Factor                         revenue growth    P-value

Sell-side (storefront)              0.38          0.082
Reverse auction                     0.61          0.020
E-procurement with catalogs         0.41          0.040
Public exchange                     0.13          0.375
Private exchange                    0.18          0.256
Forward auction                     0.19          0.257

                              Correlation with
Factor                         cost reduction    P-value

Sell-side (storefront)              0.43          0.039
Reverse auction                     0.58          0.021
E-procurement with catalogs         0.45          0.038
Public exchange                     0.01          0.780
Private exchange                    0.29          0.157
Forward auction                     0.21          0.237

TABLE 8: RESULTS OF HYPOTHESIS TESTING

                                                            Results of
                                                            Hypothesis
Hypothesis                                                   Testing

Hypothesis 1: Company size influences e-commerce             Accepted
implementation results

Hypothesis 2: Comprehensiveness of the implemented           Accepted
e-commerce solutions positively influences (improves)
implementation results

Hypothesis 3: Sell-side e-commerce solutions increase        Accepted
revenue

Hypothesis 4: Buy-side e-commerce solutions reduce cost      Accepted

Hypothesis 5: E-commerce exchange/auction solutions          Rejected
increase revenue and reduce cost

6. REFERENCES

Begin, L. and H. Boisvert, "The Internal Factors that Can make or Break E-commerce Implementation", CMA Management, 2003, April, 22-25.

Chan, C. and P. Swatman, "Management and Business Issues for B2B eCommerce Implementation", Proceedings of 35th Hawaii International Conference on Systems Sciences, 2002

Desisto, R. and A. Sarner, "Sell-Side Electronic Commerce: From Tools to Applications", Gartner, Inc., 2003, October, 1-4.

eMarketer Report on Europe E-Commerce: B2B and B2C, 2003, July, website: http://www.emarketer.com/Report.aspx?b2b_b2c_euro_jul03

Eisenmann, T. at al., Internet Business Models: Text and Cases McGraw-Hill Higher Education, New York, 2004

Govindarajulu N. at al, "Towards Theory Building in E-Commerce: Identification of Pertinent Research Stream and a Call for Further Research", Proceedings of the Second World Conference on POM and 15th Annual POM Conference Cancun, 2004, 2-17.

Hansen, F., "Global E-commerce Growth", Credit Management Magazine, Fall 2003

Kendall, J. E., & Kendall, K. E., "A Paradoxically Peaceful Coexistence Between Commerce and Ecommerce", JITTA : Journal of Information Technology Theory & Application, 2001, 3(4), 1.

Kioa, K. and T. Murphy, "ISM/Forrester Research Announce Results of Latest Report on Technology in Supply Management", www.ism.ws, 2003, October 27

Laudon, K. and C.G. Traver, E-commerce: Business, Technology, Society, Pearson Addison-Wesley, Boston, 2003

Rae, A., "Report on Survey of Council Construction-related E-Procurement Implementation", Local-eGov, 2003, 1-11.

Rayport, J. & Jaworski, B., e-Commerce McGraw-Hill/Irwin, New York, 2001.

Starr, M.K., "Application of POM to E-business: B2C E-shopping", International Journal of Operations & Production Management, 2003, 23(1). p. 105-124.

Turban, E. at al, Electronic Commerce: A Managerial Perspective, Prentice Hall, Upper Saddle River 2004.

Van Akkeren, J. and A.L.M. Cavaye, "Factors Affecting the Adoption of E-Commerce Technologies by Small Business In Australia--An Empirical Study", Australia Computer Society, 2003.

Wilkins, L., P.M.C. Swatman, and T. Castleman. "AQIS--a Preliminary Case Study of Electronic Service Delivery in a Government Department", 5th ColIECTeR Conference on Electronic Commerce, 2000 Brisbane, Queensland.

Wu, S.-I., "The Relationship Between Consumer Characteristics and Attitude Toward Online Shopping", Marketing Intelligence & Planning, 2003, 21(1), 37.

Author Profiles:

Dr. Zinovy Radovilsky earned his Ph.D. at the Scientific Research Institute

of Labor, Moscow in 1984. Currently he is a professor of management and finance at California State University, Hayward. He has published a number of papers in international and domestic referred journals. Also, Dr. Radovilsky has had an extensive consulting experience in quantitative business modeling and operations management.

Dr. Vish Hegde earned his Ph.D. at the University of Pittsburgh, Pittsburgh, PA in 1997. Currently he is an assistant professor of management and finance at California State University, Hayward. He has worked in Information Technology/ERP industries for five years prior to joining California State University, Hayward. He has an extensive consulting and product management experience with e-business/ERP software applications.

Zinovy Radovilsky, California State University, Hayward Vishwanath G. Hegde, California State University, Hayward