Profile of a Teacher

green supply chain ...environmental indicators

2009-09-27T20:28:00.000-07:00

Environmental Indicators in a green supply chain
…an empirical study in the Philippine context.

Indrani R. Halady,
Signet Capital Management Limited
Buchanan House, 3 St. James’s Square
` London, SW1Y 4JU
Email : ihalady@signetcapitalmanagement.com

Purba H. Rao
Adjunct Faculty,Calcutta Business School
Diamond Harbor Road
Bishnupur 743 503
24 Pargamas (South)
Email: purbarao@gmail.com
Abstract
The concept of green supply chains has started to be widely accepted in many corporate organizations, incorporating environmental sustainability in different phases of company operations across the entire supply chain. However there is a continuous need to measure and monitor to what extent the environmental performance is actually achieved.
To assess this performance the current paper proposes a system of environmental indicators across the supply chain, which would be practical to understand and computationally easy to implement at the industry level. To demonstrate that the system of environmental indicators indeed measure performance, the paper investigates, using an empirical approach, whether the system actually correlates with the four constructs of environmental sustainability: resource conservation, energy efficiency, reduction of hazardous waste and reduction of greenhouse gases.

The empirical approach analyzes the data collected from companies in the National Capital Region in the Philippine setting using a survey questionnaire as research instrument.

Key words: green supply chain, environmental indicators, sustainability

Environmental Indicators in a green supply chain …an empirical study in the Philippine context.

Introduction /relevance of green supply chain

Ever since the early 90’s when industry all over the world woke up to the growing relevance of sustainable development, countless business enterprises adopted environmental initiatives as an integral part of their business practices. All the same if environmental sustainability has to encompass the entire stretch of the operations of a company and include employees, suppliers, customers, waste handlers and other business partners in the greening process, an integrated supply chain approach would need to be considered. In other words the company would need to adopt a green supply chain, identifying the environmental aspects at every stage, assessing the environmental impacts associated with the aspects and designing action plans to mitigate the adverse effects on the environment if any. Thus the greening initiatives would consider the inbound logistics phase of the supply chain, production or internal supply chain, outbound logistics phase and reverse logistics phase.

In Asia, for many organizations, green supply chain approach has been a way to demonstrate their sincere commitment to sustainability. Furthermore, since company and its business partners are always considered as one single system to deliver the product or the service, any shortfall on the part of sustainability initiative from business partners is taken as the company’s failure to ensure sustainability. This makes it all the more important for state of the art companies to integrate the pollution prevention initiative in a streamlined manner along the complete supply chain.
The topic of green supply chain, what used to be called an emerging research area , is now well on its way towards becoming a well developed literature collection encompassing integrated sustainability issues as well as social and community oriented ones. The research now looks at different phases of supply chain and discusses innovative environmental initiatives which can be integrated there, such as metrics and environmental indicators to measure and monitor environmental operations.

Aside from supply chains for individual business organizations, research has also looked at supply chain issues for SMEs,(small and medium enterprises) public and non-government organizations and even for educational institutes. Some research has also looked upon the synergies between supply chain issues and sustainable development at the country level , where the authors consider supply chain strength in terms of the number and quantity of suppliers and customers in a country and relate them to sustainable development in terms of environmental performance, economic performance and even social sustainability.

Considering the supply chains related to SMEs, researchers analyzed the practices and challenges faced by SMEs to make their suppliers environmentally and socially responsible. They also aimed to develop environmental performance indicators system to measure environmental performance for specific phases of the supply chain and come up with different approaches and methodologies to evaluate and operationalize the use of metrics into the supply chain.

The Objective of the paper

Thus, though a wide array of theory and insights have been developed to integrate sustainability aspects in integrated supply chains, the authors believe that a performance assessment system to help implementation aspects of green supply chain, its evaluation and performance monitoring system have not been developed in a manner which will encompass the entire supply chain.

It is therefore the objective of this paper to propose and validate an environment performance indicator system which would capture environmental performance across the entire supply chain into an array of simple, easy to compute indicators which would help organizations, both large and small, to implement, measure and monitor the performance of green supply chain, encompassing their entire supply chain operations. The indicator system should be capable to bring in the supply chain perspective involving not just a single company but also an array of supplier companies, distributors, waste handlers, customers and other business partners interfacing the different stages of the supply chain.

In addition to measuring performance, environmental indicators also help to benchmark their own operations to that of the industry standard and even to those of a state of the art company within the same industry vertical. Further the indicators could be used as a system of communication tools for corporate environmental reporting to local regulatory bodies or as part of Global Reporting Initiative (GRI) used by many organizations worldwide (http://www.mallenbaker.net/csr/CSRfiles/GRI.html).

Some indicator systems examine relationships between managerial practices such as Quality Improvement approaches and Business Performance. Other systems bring out a strategic fit between manufacturing decisions and other strategies . There are also other indicator systems that explore different approaches to strategic fit between operations strategy, financial strategy and the competitive business environment.

Methodology for developing Environment Indicators for Green supply chain

Emanating from substantial research on environmental indicators and environmental performance, we propose a system of environmental indicators which would be easy to compute by companies both large and small … but this time encompassing the entire supply chain with an objective of greening it. Based on existing research, many environmental indicators could be proposed. However, the authors adopted the indicator system for the green supply chain which had a similar structure to the system proposed for corporate environmental initiatives, which, again, was already tried and tested in the Philippine context (Rao,2006,2008).The indicators, thus proposed were grouped under four constructs, each construct relating to a specific phase of the supply chain, such as construct for Inbound logistics, construct for Production and internal supply chain, construct for outbound supply chain and the construct for Reverse logistics. Hence the indicators pertain to each phase of the supply chain, as shown below.

Indicators for each phase of the supply chain.

Inbound logistics
(EI1) Proportion of recycled materials to total material input in %
(EI2) Proportion of recyclable materials to total material input
(EI3) Proportion of reusable material to total material input
(EI4) Proportion of hazardous material to total material input
(EI5) Proportion of suppliers with environmental policy
(EI6) Proportion of suppliers for whom environmental audit
is conducted by company

Production/internal logistics
(EI7) Raw material efficiency =proportion of raw material in ton
to total product output in ton (%)
(EI8) Proportion of cost of energy in production to total value of
output (%)
(EI9) Water efficiency=proportion of total water consumption to
value of total output (%)
(EI10) Proportion of material recycled in the production phase to total
value of output(%)
(EI11) Proportion = proportion of total cost of renewable energy in
production to total value of output (%)

Outbound logistics (EI12) Proportion of total solid waste to total output in value (%)
(EI13) Proportion of total solid waste for recycling to total
product output (%)
(EI14) Packaging proportion = Proportion of total value of
packaging to total output
(EI15) Proportion of hazardous waste produced to total product
output
(EI16) Volume of air emissions per year (NOx, Sox, CO2, VOC) (EI17) Proportion of total wastewater produced to total output
(EI18) Proportion of total wastewater treated to total product
output.
(EI19) Use of renewable energy, electric and natural gas run
Vehicles for distribution of finished products

Reverse logistics phase (EI20) Proportion of output recovered from customers after use
and put back in the supply chain, if any

The indicators and supply chain perspective.
The indicators proposed above do not take up a single company perspective but considers, in addition to the main company, a set of suppliers, distributors, waste handlers, customers and other business partners impacting the indicators. This aspect of including the impacts of different associated companies in the indicators for the supply chain can be observed by seeing how they affect the indicators. For instance for the indicators under the construct of Inbound Logistics their levels would be affected significantly by supplier companies supplying recycled materials, reusable materials, hazardous materials and so on. Again for indicators under the construct of Outbound Logistics, their levels would be impacted by waste handling companies treating the waste water generated, distributors companies using cleaner energy in transportation, waste contractors picking up hazardous waste and so on.

To give a specific example the indicator EI1 measures proportion of recycled material to total input, the recycled material being supplied by supplier companies. Again indicator EI20 measures the percentage of output recovered from the customers/customers/customer companies, which would be significantly impacted by the customers cooperating and allowing the output to be recovered from them after use.

The objective of the paper, as explained above, was to develop environmental indicators on the green supply chain which should be able to measure and monitor the environmental performance across the entire supply chain. This led the authors to define environmental performance in terms of tenets accepted and available in existing literature. For this, the authors followed the guidelines/ postulates for environmentally responsible products brought out by industry, as proposed by Asian Development Bank(Environmentally Responsible Procurement, A Reference Guide for Better Practices, 2007). These postulates translated in concrete terms as (a) conservation of resources (b) energy efficiency (c) reduction of hazardous waste generation, solid liquid and gas, and (d) reduction of greenhouse emission. In the following paragraphs the paper tries to link the 20 indicators for green supply chain to these four factors, which essentially lead to pollution prevention and environmental sustainability.

Predicting the Relative Values of attributes in social entrepreneurial opportunities

2008-04-20T06:29:00.000-07:00

Predicting the Relative Values of attributes in social entrepreneurial opportunities….from the perspective of social entrepreneur.

… an application in conjoint analysis

‘Social entrepreneurship is a term used to describe innovative approaches to solve social problems’ ( Desa, Geoffrey, ISERC, 2007).

Recently, this topic has gained increased attention in conferences, case research and funding agencies interested in the topic. Researchers such as Drayton, founder of Asoka organization, one of the biggest organizations to promote social entrepreneurship in today’s world, described this topic as a body of innovative approaches to solve social problems. Subsequent research has further described social entrepreneurship as a process where the individual, the social entrepreneur, plays a significant role looking at attributes of the social entrepreneurship opportunity, evaluating them and then deciding whether to adopt these opportunities and turn it around to a real life enterprise.

According to Morato (2006) a social entrepreneur is someone who creates and operationalizes an organization which is sustainable on one hand and , on the other hand ,promotes livlihood opportunities for a community of people who need them . In other words the characteristics of a social enterprise will be distinctly different from traditional business enterprise in terms of primary stakeholders or beneficiaries , objectives and enterprise philosophies (Dacanay ). In traditional business enterprise the primary stakeholders and beneficiaries are its stockholders like the owners and people who have invested in the business. In social enterprise however, the primary beneficiaries could be a community or group of people who may not own the enterprise at all. Again the primary objective in a traditional business enterprise has profit bottom line. A social enterprise on the other hand strives to improve the quality of life for a community or works towards empowerment of a group. Not that financial sustainability is not required in a social enterprise but it is not the reason for its existence .

In terms of enterprise philosophy traditional business enterprise accumulates wealth for its owners whereas in social enterprise wealth generated is distributed back to the community.

The distinction between a social enterprise and a regular enterprise is not always clearly definable. In fact there are various stages between purely social to purely economic enterprises, where at each stage an enterprise has a component of social and a component of economic or commercial values.

The field of entrepreneurship is relatively new as compared to many other fields on Management .However, in the recent few years there has been some significant research in the field , where many researchers have focused on to exploring what makes this field distinctive from the other fields of enquiry. In the earlier years research also tried to differentiate entrepreneurs from other individuals in the population. They were looked upon as having special personality features , capable on innovation , attitude/ endurance towards risk, leadership potentials and strong business acumen which enabled them to sense an opportunity even where it might not be apparent.

These features it was thought ,would make an individual emerge as an entrepreneur creating and leading ones own enterprise.

However, many such research efforts were relatively unsuccessful in trying to explain entrepreneurship ( Gartner, 1990 )

Traditionally there is also quite an extensive research on what kind of entrepreneurial opportunities are perceived as attractive , which lead individuals to become entrepreneurs. In fact it is hypothesized that entrepreneurial opportunities are often objective in nature , available to everyone , but perceived in different lights depending upon the personality traits on the potential entrepreneur who looks at them. Such entrepreneurial opportunities start as what are called ‘third party opportunities’

( McMuller and Shepherd, 2006 ) which refer to opportunities which do not look like opportunities for anyone and everyone in the market but with individuals with right qualities they unravel their potential. These third party opportunities become first party opportunities if they emerge as specially appealing or stimulating to a particular individual and the opportunity becomes real and ultimately gets transformed to the start of an enterprise.

In analyzing entrepreneurial opportunities which are considered or are available to the prospective entrepreneurs research does not often include the social attributes on entrepreneurial opportunities. However, there is a relatively small body of research who have considered social entrepreneurship initiatives of entrepreneurs in different social and commercial context.

Traditionally entrepreneurs are motivated by both economic and non-economic factors. For instance many entrepreneurs start their own venture even when they believe it would result in lower economic gain than some other career options.( Amit, MacCrimmon et al. 2000) . Also self respect , achievement of personal and professional ideals may be more valued by entrepreneurs than making money ( Guerrier and MacMillan 1981, Corman, Perles et al. 1988). Then there are other entrepreneurs who are community focused because of their motives around welfare issues of the community .

Whatever definition one adopts for social entrepreneurship the main concept still implies that social entrepreneurship is any form of entrepreneurship that has more than singular goal of profit maximization. Rather than attaining economic gain, social entrepreneurship represents centering on identifying, addressing and solving a wide variety of social problems ( Drayton, 2002 ). This concept also relates to opportunities for reducing negative impact of business and creating social improvement in the process (Mair and Marti 2006; Zahra, Gedajlovic et al. 2006).

Having discussed the concepts leading social enterprise and also a social entrepreneur , one acknowledges in any case that for a social enterprise to exist and survive , it still needs to be economically feasible, sustainable and contain growth potential. The factor which differentiates it is whether the economic goals are the only goals in the enterprise or whether there are some other goals beyond economics, which drive the enterprise.

Along with defining social enterprises and thereafter social entrepreneurs, research has further considered characteristics, values, attitudes and personality traits of enterprising individuals who take up the prime mover seat in a social enterprise. For instance, past experiences, many of them early in life, distinguish a social entrepreneur from others (Barendsen and Gardner, 2004). Social ideals (Sims and Robonson, 2005 ) personal credibility in the form of past record of success which lead to the entrepreneur’s ability/ aptitude to mobilize and access resources (Sparie and Lerner ,2006, Thompson 2002) etc. all make up a social entrepreneur.

All the same, though there is a widespread approach in social entrepreneurship research focusing on person-centric perspective distinguishing a social entrepreneur from other persons in the population, another approach to social entrepreneurship research also exists, moving away from individual to looking at the role of characteristics in opportunities that represent potential for profit making in setting up commercial enterprise or social change in the case of social enterprise (Shane, Locke et al).

These opportunities possess attributes to address either the economic motives of the potential entrepreneur or social missions of the potential social entrepreneur.

It would be interesting to identify and evaluate the relative values of these attributes to the potential entrepreneur which eventually provide the ‘tipping point’ to lead the individual actually becoming an entrepreneur… either a commercial entrepreneur generating economic growth or social entrepreneur bringing in social change.

In this paper on social entrepreneurship it would be our objective to specifically identify and evaluate relative values of the characteristics in entrepreneurial opportunities which lead or are found attractive enough by individual to becoming a social entrepreneur.

2007-12-09T06:41:00.000-08:00

Predictive Modeling in application software industry…
SoftwareAsia Inc.

The company and its new business model.

SoftwareAsia (SWA) is an I.T service provider, focusing on delivering technology driven solutions and services to a wide-spectrum of industry. SWA has been in the industry for more than six years with offices in the Philippines.The company provides flexible service offerings that leverage technology from mainstream to cutting edge solutions. With proven methodologies, tools and best practices we help ensure the successful implementation of technologies in complex project environments. The products offered by the company to its many clients are softwares for payroll system, financial management information systems, customer relationship management system, document management system, fixed asset management system, supplies and inventory management system, corporate portals and so on.

The company has been performing quite well ,though initially it faced some ROI problems , essentially because of difficulty in finding a comprehensive client base. The difficulty was over come by the founding team of the company establishing alliances with a software training group where the founders offered recruitment services for the graduates of the school.

Recently, the company has been thinking of using a new revenue model ,called Software as a Service (SaaS) in the application software industry in the country. The SaaS model, also often referred to as the rental model for software services ,is different from the traditional model where revenue is earned by selling software as a product in which customer makes a one time payment for permanent ownership of the software. The SaaS model offers the software to the customer in the form of a service . The customer does not own the software but simply use it and pay for the usage periodically based on the volume of usage. However whether SaaS revenue model is acceptable and needed in the Philippines is yet to be established and SWA is keen to evaluate this proposition.

The Business Challenge for SaaS Revenue Model

Recently, the Government of Philippine has launched its SME agenda with the objective to enhance their operations and make them more competitive by providing them with the necessary financial, marketing and technological assistance. SMEs are the economic backbone of the country and 99.6 % of the total number of registered firms in the Philippines. SWA feels that the SaaS model is especially suitable for the SME businesses because of its low cost of ownership and high and robust quality ,not given to breaking down, of the software product. Since the SMEs have comparatively less economic resources at their disposal as compared to large corporations ,thy are usually not willing to take the risk of owning a software product that has a small lifetime , as it requires frequent upgrades or willing to make upfront investments in software product without testing how well it will meet their requirements. Hence SMEs might want to try out the software on the rental basis. This would also enable them to switch their vendor in case they do not feel satisfied with the product. Further SaaS would even reduce the cost of ownership by eliminating the need for additional expenditure after the software procurement such as professional fees, infrastructure, hardware, training costs etc.
Value proposition to the application software industry

SaaS is a new concept in the application software industry. Adoption of this model would lead to the development of products that promise low cost of ownership, platform independence and secure transaction environment to users. Low cost of ownership emanates from the fact that users of the software will not have own the software anymore. They will just have to pay the rent for its usage. This will increase the bargaining power of the customers as they will not be tied to the software for life. They will have the option to switch to other vendors if they are not satisfied with the quality of product/service being provided by the vendor. This will put an increased pressure on the vendors to offer quality products at low cost. Since the infrastructure and product development cost would be borne by the vendors they will continuously try and improve their method of product development in order to curtail costs and economies of scale. Platform independence implies that the software will not be dependent on a particular technology for its deployment. This will save the customers from the need for extra investment in technical infrastructure and supporting software to enable them to access applications. The secure transaction environment is necessary as the data repository would be hosted by the vendors.
All these features ,namely the provision of low cost ,high quality, highly secure, platform independent application software, promising anytime anywhere access and developed using efficient means of production ,would add to the maturity of the application software industry. This will change the way revenue is earned in the industry .Time to market, accessibility and quality of service would also be critical factors in this approach.

Though convinced of the importance and relevance of the SaaS model in the Philippine application software industry ,before adopting the model within their own operations SWA Inc. decided to conduct a market analysis involving the acceptance of the model to its proposed target market. Thus they conducted a market research exercise where the primary sources of data would comprise surveys and interviews. The survey would help to determine consumer satisfaction, needs analysis , defining the effective customer segments and subsequently making an inference about the target market. The secondary sources of data would include study of relevant literature on SaaS and application software industry, documentation on internet ,research reports from global research agencies and so on.

For the primary survey data SWA designed a questionnaire to be administered to a sampling frame of SMEs which had the following components:
(a) a demographic section for SME company
(b) level of satisfaction on various features of software they have purchased and used
( c) their specific software needs
(d) awareness about the concept of using software on a rental basis
(e) extent of willingness to use such software on rental basis ,etc.

Questionnaire

Objective: to understand the market acceptability of SaaS

Please rate the following software attributes on your level of satisfaction with your existing software ,on 5-point scale:

1= not satisfied
2= neutral
3 = somewhat satisfied
4= satisfied
5= very satisfied

(Price of software)
(I) (a)How satisfied are you on the cost of procurement of your basic existing software.
(b) How satisfied are you on the high cost of availing professional services
( c) How satisfied are you on the high cost of application maintenance and support
(d) How satisfied are you on the high cost of training associates to use software application
(e) How satisfied are you on the high cost of IT infrastructure and hardware

(Quality of software)

(II) (f) How satisfied are you with the software application meeting the
specification
(g) How satisfied are you that the results of the software application are
accurate
(h) How satisfied are you that the results of software application are
consistent with for same values of input
( I )How satisfied are you with the security of data and information
offered by the application

(Usability of software)

(III) (j) How satisfied are you that the application can be accessed anywhere
anytime
(k) How satisfied are you that the program is able to generate desired reports
(l) How satisfied are you that the reports are well formatted and easy to
comprehend
(m) How satisfied are you that the software application can be easily customized to suit your requirements
(n) How satisfied are you that the software can handle complex transactions
(o) How satisfied are you that the software can be deployed on any technological platform
(p) How satisfied are you that the software offers easy navigation capability
(q) How satisfied are you that the software can be easily deployed

(Delivery of software)

(IV) (r )How satisfied are you that the vendor’s technical support personnel are prompt and knowledgeable
(s) How satisfied are you that the vendor adheres to the schedule in terms
of delivery of application

(V) Which of the following applications are you most likely to procure within the
The next one-year.

(1) Financial Management packages
(2) Payroll Systems
(3) Supplies and inventory management systems
(4) CRM systems

(VI) How aware are you about the concept of using software on the rental basis

(1) not aware
(2) heard about it
(3) somewhat aware
(4) well aware

(V) How willing are you to use software application on a pay-per-use basis

Willing Not willing

(VI) How much would be your budget for such a service offer

<10,000.month
10,000 to 15,000 per month
15,000 to 20,000 per month
20,000 to 25,000 per month
25,000 to 30,000 per month
(VII) Your company’s annual turnover

50 M to 100 M
100 M to 200 M
200 M to 300 M
300 M to 400 M
400M to 500 M

(VIII) No of people in your company …………………
(IX) Years of operation of your company ……………..
(X) Is your company export oriented yes/no

Empirical Research

The empirical research was conducted to obtain primary data from the target market comprising SMEs in the National Capital Region , to understand their software needs ,level of satisfaction on the various software features they have been using so far ,awareness of using software on rental basis and willingness to use the SaaS model.

To obtain a representative sample ,a multistage sampling procedure was used whereby the NCR region was looked upon comprising 50 different sub-regions. A random sample of 10 sub-regions were selected. Within each sub-region, thus selected, cluster sampling was used to select 10 SMEs. For the cluster sampling within each sub-region , SME clusters were looked upon within the sub-region and from the clusters any 10 SME were selected. From the sample of SMEs thus selected, 112 in number, the questionnaire was requested to be answered by CIO, chief information officer . For the survey , a researcher took an appointment with CIO and asked him/her the questions in the survey. So, the survey was actually filled by the researcher which ensured the completeness and authenticity of the process.

Thus a total of 112 completed questionnaires were obtained ,which led to a margin of error of 9 % under the confidence level of 95 %.

Towards Predictive Modeling based on the data

Testing the Reliability /Consistency of the different factors measured.

In the questionnaire the respondent SMEs were asked to give their levels of satisfaction on different constructs such as :
Price of software
Quality of software
Usability of software
Delivery of software .

In addition ,of course, the SME is asked to list their likely application softwares, awareness, proposed budget for SaaS service offer , annual turnover, size of company ,years of operation and willingness to buy.

The above constructs, often called latent constructs, have certain indicators associated with them, which are the questions under each construct.

For instance the Price construct is measured by cost of procurement, cost of availing professional services, cost of application maintenance, cost of training and high cost of infrastructure and hardware.

Similarly the other constructs have other indicator variables associated with them, as given in the questionnaire.

Before carrying out data analysis on the constructs ,first their reliability and consistency factors were evaluated. This was done by checking if the indicator variables under each construct measured the same feature. In other words , SWA checked high highly the items under each construct were interrelated. Since under Price construct there were five items their inter relatedness needed to be measured. For this, bi-variate correlation was not sufficient because this feature only checked correlation two by two.

To check the inter relatedness, there fore Cronbach’s Alpha estimate was used ,which measured the overall relatedness of all items under a construct. The Cronbach’s alpha should work out to > 0.8. If this does not hold , certain items are removed from the construct so that ultimately the alpha is greater than 0.8.

The Final Cronbach’s alpha values for the different constructs and the associated indicator variables ,which consistently inter related with one another ,are as follows:

Construct Cronbach’s Alpha Indicator variable associated
==========================================================
Price 0.8005 cost of procurement
Professional services
Maintenance &support
Training

Quality 0.8763 meeting specification
Accurate
Security

Usability 0.8173 desired reports
Easy to comprehend
Customized
Technological platform
Navigation capability
Easily deployed

Delivery 0.7373 prompt
Terms of delivery

Significance of satisfaction:

For the four constructs, the level of satisfaction was:
Significant for the first three ( taking the cut off value as 4) but not significant for delivery.

Analysis of variance (ANOVA):

In this analysis ,the company wanted to determine the distinct SME profile, if any, for the two levels of question 5. willing/not willing to use SaaS model for softwares. Thus , for ANOVA, the grouping variable was taken as willingness to use software application on pay-per-use basis and the dependent variables were :

---------------------------------------------------------------------------------------------------------
Dependent variable F-value significance
---------------------------------------------------------------------------------------------------------
Price 3.075 0.082
Quality 38.509 0.000
Usability 11.543 0.001
Delivery 0.002 0.968
Aware 0.730 0.395
Budget 8.844 0.004
Function 0.017 0.896
Turnover 1.910 0.170
Years of operation 232.281 0.000
Number of employees 21.422 0.000
Export 0.535 0.466

Thus there are two categories of SMEs, those willing to use and those not willing.
These two categories differ in their level of satisfaction on quality and usability. They also differ in their budget for soft wares, years of operation and size in terms of number of employees . For the other variables there is no significant differences in the two categories.

Linear Discriminant Analysis (LDA) and Predictive Modeling

Linear Discriminant Analysis was used to obtain the distinct profile of the two SME segments, those willing to use SaaS model and those ,not willing.

Here the equation used for the predictive modeling is :

D= b0 +b1X1 + b2X2 +b3X3 ….

D= 1, if SME is willing
0, if SME not willing.

The independent variables are :
Price, Quality, Usablity, Delivery, Budget, Turnover, No of employees, years of operation , awareness, function where software may be used .

The discriminant analysis tries to come out with a function which would discriminate /separate between the two segments in such a way that their within group variation is small but between groups variation is large.

Thus the Wilk’s lambda ,measuring within group variation to between group variation ,is as small as possible , where as eigen value measuring between group variation to total variation ,is as large as possible.

Summary of canonical discriminant function

Eigenvalue % of variance canonical correlation Wilk’s Lambda Chi-sq signif
2.946 100.0 0.864 0.253 142.76 .000

Structure Matrix

Independent Variable canonical correlation
==========================================
Years of operation .835
Quality -.384
No of employees .266
Usability -.212
Budget -.168
Price -.100
Turnover -.077
Aware .047
Delivery .012
Function -.001
In the above table we consider only the top 5 variables .
Thus the SMEs willing to use SaaS model are those with longer number of years of operation . Thus they have been operating for many years. Thus they are older companies.

They are also larger companies with larger number of employees.

They are not satisfied with quality and usability and have smaller budgets for Software use.

Hence if SWA would like to promote a marketing campaign for SaaS model, they should target companies with larger number of years of operation, older companies ,larger number of employees but perhaps having a small budget for softwares.
These should also be the companies which are not satisfied with price, quality and usability aspects of their existing softwares.

If the above equation for discriminant is used then the predictive power of the equation will be about 93.7 %; in the sense that 93.7% of the time the prediction of willingness/ unwillingness would match the actual happening.

Using CHAID for predicting customers willing to buy.

As mentioned and explained previously, CHAID is a combination of heuristic as well as statistical method which examines relationships between many categorical predictor variables and a categorical, usually nominal, target variable. It applies the Chi-square test on independence, also called Contingency table ,between the target variable and each of the predictor independent variable using the multi-way cross tab table . The null hypothesis H0 : the two variables are independent .

This iterative process works with repeated application of Chi square test between target variable Y and each one of the different predictor variables. The predictor variable which gives the smallest p-value provides the basis for first partition from the root node. Thereafter the tree ‘grows’ following the same iterative process of partitioning by the Chi-square testing.

The process of identifying the predictor variable with the smallest p-value is called the Bon Ferroni approximation.

Using CHAID for SaaS model for software application, the target variable used was, once again as in discriminant analysis , willingness to use .
The decision tress emerges with a few nodes only, because of the small size sample.

The index percentage levels for the three terminal nodes are :

Node index percentage

3 326.8 %
2 242.4 %
1 8.7 %

Hence the software company should target the nodes 2 and 3, which make up about 30.36 % of the market, with node 3 giving a response rate of 96.30 % and node 2 giving a response rate of 71.43 %.
These two segments conform to companies with years of operation 9 and higher , implying the marketing campaign should be targeted to SMEs operating for more than 9 years.

2007-12-08T07:37:00.000-08:00

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