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CHAPTER – 2

REVIEW OF LITERATURE, OBJECTIVES AND

RESEARCH METHODOLOGY

2.1 Marketing Information System (MKIS)

The firms have functional information systems that consist of Marketing IS,

Manufacturing IS, Finance IS, Human Resource IS, and Information Resource IS

(McLeod and Schell, 2001). The firms have to study the manager's needs and design a

Marketing Information System that really meets their needs (kotler and Keller, 2012) (65)

.

Kotler and Armstrong (2010), pointed out that there is no one MKIS that will serve all

organizations because of the unique information requirements of different organizations

which are composed of sub-systems and they have been built over a long period of time.

From the marketing management point of view, MKIS is a tool for managing marketing

information, marketing research, modeling marketing transactions, decision making in

marketing, planning marketing strategy and tactics, budgeting, analyzing different courses

of action, and reporting and control(Li, 1995) and (Higby and Farah, 1991)(1)

.

"Without good marketing information, managers have to use intuition or guesses-

and in today's fast-changing and competitive markets, this invites failure." (McCarthy and

Perreault, 1993). There are some firms which lack information sophistication, and others

do not have Marketing Research Department, and others do their work on a routine basis.

Moreover, there are some managers who complain about the lack of information, getting

the needed information late, and getting too much information that they can't use. All the

firms around the globe should organize the information and disseminate in a timely

manner continuously.

The general system elements for any MKIS include a data acquisition system,

database management system, graphical and statistical analysis tools, model base,

directories (specific data elements/information classification schemes) and retrieval

systems (Amaravadi et al., 1995).

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2.2 Definitions

Marketing Information System (MKIS) was first seen by Cox and Good (1967) as

a set of procedures and methods for the regular planned analysis and presentation of

information for use in making marketing decisions. The purpose of the earliest marketing

systems was to gather, sort, analyze, evaluate and distribute pertinent, timely and accurate

information for marketing decision makers to improve their planning, implementation and

control (Talvinen, 1995).

Cox (1964)(2)

, defined MKIS as � a structured, interacting complex of persons,

machines and procedures designed to generate an orderly flow of pertinent information,

collected from both intra- and extra-firm sources, for use as the basis for decision making

in specified responsibility areas of marketing management.

O‘Brien et al., (1995)(3)

"An MKIS is an organized set of data that is analyzed

through reports and statistical routines and models on an ongoing basis. The data are

transformed into information that allows the marketing manager to make better decisions

and perform better planning and budgeting”.

"An MKIS is a computerized system that is designed to provide an organized flow of

information to enable and support the marketing activities of an organization", (Harmon,

2003).

All of these descriptions envisioned the MKIS as an information processor,

gathering data and information from the marketing environment, processing that data and

information, and providing the results to marketing managers in the form of management

information. The managers would act on the information and make decisions that affect

the environment as well as the firm's operations (Li et al., 1995).

2. 3 Benefits and Importance of MKIS

One of the very first benefits that a company derives from the use of IT-based

MKIS is improvements in the reporting system. Information processing becomes faster

and the company‘s management is able to relate pertinent information from different

sources within the organization (Van Bruggen et al., 2001). Such information would be

almost impossible to bring together in a meaningfully and integrated fashion without the

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necessary IT infrastructure. The purpose of MKIS applications is to integrate inputs from

various organizational functions into a holistic and meaningful map of company‘s

activities, depicting its interactions with suppliers, customers, and so on. As a result of

doing this in a timely fashion, decision making is enhanced by relying more on facts than

gut-feeling and intuition (Van Bruggen et al., 1998; Talvinen and Saarinen, 1995). This is

a major prerequisite for developing realistic and successful marketing plans (McDonald

and Payne, 2005), which in turn affects both the company‘s marketing planning process

and the outcome of this process (Amaravadi et al., 1995; O‘Brien et al., 1995). Such

improvements in the marketing planning effort have, among many other consequences, a

positive direct effect on marketing operations (Baker, 2001). As companies assimilate the

IT-based MKIS, they eventually become capable of transforming marketing intelligence

into concrete benefits for their customers (Brady et al., 2002), which in turn allows them

to improve their marketing operations.

MKIS gives the management the opportunity to make better decisions by

providing a flow of information continuously, such as prices, advertising expenditures,

sales, competition, and distribution expenses (Pride and Ferrell, 1987). MKIS has been a

tool for analyzing both internal and external effectiveness of marketing and for

controlling marketing activities and environment. MKIS can be seen as a natural

expansion of traditional market research (Heiser et al. , 1983). From the planning point of

view, analyzed data in MKIS are used as a basis for planning, but planning itself is done

in other systems and often manually (Talvinen, 1995). Implementation and control of

these plans is then performed with the help of management and operational MKIS. The

MKIS can enable marketers to collaborate with customers on product designs and

requirements. MKIS systems are designed to be comprehensive and flexible in nature and

to integrate with each other functionally. They are formal, forward looking and essential

to the organization‘s ability to create competitive advantage. The MKIS is the firm‘s

�window on the world and, increasingly, it is the primary customer interface (Harmon,

2003). An MKIS can support managers in their marketing decision due to the fact that

MKIS provide integration between functional departments or divisions (O‘Brien et al.,

1995). MKIS plays a major role in the international marketing decisions support system.

MKIS involves data collection, data management, data storing and retrieving, processing

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data into useful information, and disseminating information to people inside the firm who

need the information (Albaum and Duerr, 2008).

An MKIS organizes the data that has been available to the firm in order for it to be

available when needed. Most of the companies have information processing specialists

who are assigned for making standard reports from the available data to help managers

make better decisions (Perreault and McCarthy, 1993).

Amaravadi et al. (1995) mentioned,(4)

"Intelligent Marketing Information

System (IMKIS) has the potential to address some of the pressing concerns facing

marketers today. It could help in analyzing product features with customer data,

evaluating channel and pricing options, creating and testing promotion plans, gaining

instant feedback on concepts and plans, and moving marketing plans rapidly into

production".

According to Harmon (2003)(5)

, the primary benefits of the MKIS can be useful

in the areas of functional integration, market monitoring, strategy development, and

strategy implementation.

• Functional integration: The MKIS enables the coordination of activities within the

marketing department and between marketing and other organizational functions.

• Market Monitoring: Through the use of market research and marketing intelligence

activities the MKIS can enable the identification of emerging market segments, and the

monitoring of the market environment for changes in consumer behavior, competitor

activities, new technologies, economic conditions and Governmental policies.

• Strategy Development. The MKIS provides the information necessary to develop

marketing strategy. It supports strategy development for new products, product

positioning, marketing, pricing, personal selling, distribution, customer service and

partnerships and alliances.

• Strategy Implementation. The MKIS provides support for product launches, enables the

coordination of marketing strategies, and is an integral part of sales force automation

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(SFA), customer relationship management (CRM), and customer service systems

implementation. The MKIS enables decision makers to more effectively manage the

sales force as well as customer relationships.

There are three roles for the marketing information system according to Assael

(1993), which are data collection, analysis, and dissemination. The MKIS must be able to

collect relevant data from different sources such as customers, competition, and

Government. At the mean time, the MKIS must be able to analyze the data, and

disseminate the data to the management and the departments in the firm (Assael, 1993).

2.4 MKIS Functions

Kotler and Armstrong (2010)(6)

. The functions of MKIS are :

i. Identify information needs.

ii. Gathering information from different sources.

iii. Data processing and preparing the information for use.

iv. Disseminating information to the decision makers.

v. Saving and recording the information.

2.5 Types of Marketing Information

A Marketing Information System supplies three types of information (scribd.com,

2011):

� Recurrent Information: The data that MKIS supplies which includes data such as

sales, Market Share, sales call reports, inventory levels, payables, and receivables.

which are made available regularly. Information on customer awareness of company‘s

brands, advertising campaigns and similar data on close competitors can also be

provided.

� Monitoring Information: The data obtained from regular scanning of certain sources

such as trade journals and other publications. Here relevant data from external

environment is captured to monitor changes and trends related to marketing situation.

Data about competitors can also be part of this category.

� Problem related or customized information: Developed in response to some

specific requirement related to a marketing problem or any particular data requested

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by a manager. Primary Data or Secondary Data (or both) are collected through survey

Research in response to specific need.

2.6 Factors helped in the spread of MKIS

As seen of the benefits and importance of MKIS, there are some reasons why

MKIS is widely spread and used by the organizations. According to Alzabi (2010), there

are five factors helped in the spread of MKIS:

i. Restrictions on the time allocated for the manager to make decisions and the speed

needed to make many decisions.

ii. The diversity and complexity of marketing activities and it's increase in depth.

iii. Information revolution and stunning development in information technology and

computers.

iv. The growing disconnect with consumers due to the lack of adequate knowledge of

management of their expectations, needs and desires.

v. Deficit in energy and other raw material resources necessary for the industry.

2.7 Difficulties of MKIS

"Setting up a MKIS requires a significant investment of time and money. Trained

personnel are needed to maintain and analyze the data collected in the system. Vast

amounts of data can be readily obtained with computerized systems; therefore, businesses

sometimes have to prioritize the kind of information that is most useful to them." (Farese

et al., 2003).

2.8 Designing of MKIS

Companies must design effective Marketing Information Systems that give

managers the right information, in the right form, at the right time to help them make

good marketing decisions (Armstrong and Kotler, 2007). There is no one MKIS that is

suitable for all companies, that is the reason why the companies design their system on a

way that will best fit the needs. According to Alzabi (2010), there are some factors that

has to be taken in consideration when building the MKIS. These factors are:

• How to reach and get the needed data?

• A continuous flow of information, and input it in the system in a timely fashion.

• The ability to provide the reports to the management in a way that will help in the

decision making process.

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• The system must be flexible, which means that the system will be able to have

some modifications whenever needed.

• The system designer should be one of the decision makers in the firm.

Richard B. Rosecky (1986)(7)

identified delayed sales information at the producer

level can cause inappropriate sales estimates; mistimed promotion efforts, inadequate

channel inventory levels and other marketing dysfunctions.

Edvard Philip Bovich (1987) (8)

, through an experimental inquiry, explored the

effects of usage of computerized decision support system on marketing management

decision-making process and decision quality. Experienced and specially trained

marketing planners participated in a comprehensive, realistic computerized product

management simulation.

The tactical plans were entered into the computerized simulation to derive short-

term corporate performance results. The experiment showed that the subjects with

computer support performed well.

Van Engelen and Johannes Marie Lucien (1989)(9)

identified that the drastic

developments in information technology have the potential of bringing forth-new

strategic (marketing) opportunities. A marketing system for instance, will serve as a

diagnostic tool for analyzing a full array of marketing problems. An empirical study was

conducted. It proved that the hypothesized relation exists between marketing strategy and

the information system with the product market contribution.

Gaillynn Cook (1990)(10)

addressed the research problem – “does and integrated

computer based information system facilitate coordination”. They opined that information

technology may be used not only to improve decision – making or logistics, but also help

to manage customer relationships. There is a necessity to use “high-powered analytical

tools” with specialized interactive marketing communication techniques.

Jiro Kokuryo (1992)(11)

described how information technology triggers the

reorganization of logistics systems and specifically, the EDI based Quick Response (QR)

systems being implemented. Laboratory experiment was conducted to test the effects of

sharing of marketing data, decision models and feed back with production managers.

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The results indicated that sharing marketing feedback, and decision models

increased efficiency of decision making above the control level.

George Day and Rashi Glazer (1994)(12)

opined that, the developments in

information systems that unleashed the date deluge have also enhanced the ability of

organizations to learn about their markets. The feasible organization changes that can

overcome impediments and ensure competitive advantage can be realized from the

investment in information system.

2.9 Development of MKIS

The development considerations include top management support, staff

knowledge and skills, outsourcing and end-user computing.

Donald F. Cox and Robert E Good (1967)(13)

presented a brief review of some

of the characteristics and advantages of sophisticated MIS and the current “State of

thought”. They identified some of the key decisions, which must be made by top

management in the MIS development process (it will help the managers decisions about

pricing, advertising, promotion, product policy, sales force effort and support.

Gernot Bernhand Langle (1988)(14)

conducted a study which focused on

knowledge which relates to a specific functional area of business (such as accounting,

manufacturing or marketing) and the presence or absence of some firm’s specific domain

knowledge in IS development. His specific study was an empirical investigation

involving eight experienced business system analysts. Each subject was asked to analyze

and design two information systems. One in a familiar area of business, the other in an

unfamiliar area of business. Subjects were instructed to think about during the tasks and

their verbalizations were tape recorded and transcribed for analysis. The results indicated

that the presence of function specific domain knowledge affected the construction of

representation as well as modeling, discovery and validation process. Subjects with

function specific domain knowledge were found to (1). Build representations considering

a large number of facts and concepts relating to the information system application

domains, (2). Discover and validate the representations requesting additional domain

specific information more frequently; and (3). Model the information system utilizing

analogical reasoning more often than the subjects without function specific domain

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knowledge. Interpretation of results suggests that when experienced system analyst

possesses function specific domain knowledge, they are more likely to construct accurate

and complete system representation and exhibit focused and efficient information

gathering behavior.

Robber C. Blattberg, and Byong-Do Kim and Jiangming Ye (1990, 1992)(15)

presented a framework for “Mass Produced”. Mass produced models are statistical

analyses of large databases where literally thousands of models are created for a single

data set with little or no human intervention. They described a typical application of

MDDS development of a price simulator for setting retail prices across many items in a

product category. They discussed the requirements necessary for models to be mass-

produced are marketing, direct marketing and customer relationship management.

Somendra Pant and HUS. Cheng (1997)(16)

reviewed the business use of internet

technology and identified that there is a lack of stable models and framework to plan for

incorporating it in business. He proposed a push model for internet strategy planning. In

actualizing this “Push” model into a concrete planning framework, through internet based

information system they made use of a reference model. This framework is empirically

tested in two industrial situations. In the Korea Longa term Bank (KLB) case, the

reference model is used to generate internet goals for the bank and, subsequently, to

redesign their processes. Based on the initial plan generated for the bank, they have

embarked on establishing an internet based online bank and are tested for the rest of the

planning framework. Second case was that of study of a Conglomerate Heavy Machinery

and Shipbuilder, Samsung Heavy Industries Company Limited (SHL) of Korea.

Additional cases were taken from literature and usefulness of reference model and

planning frame work established.

Myungoog Cheon and Varun Grover and James Teng (1992)(17)

developed a

contingency model of outsourcing from the literature. The following hypotheses were

tested and found.

� Supported Organizational attributes influence the change in the extent of an

organization’s outsourcing of ‘IS’ functions.

� Success of outsourcing is dependent upon both the change in degree of ‘IS’

outsourcing and the quality of outsourcing implementation.

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The major findings are summarized below.

• The change in the degree of IS outsourcing is determined by gaps in information

quality, IS supporting quality, IS cost effectiveness and financial performance.

• The quality of outsourcing service providers and the nature of partnerships with

them are implementation factors determining the degree of outsourcing success;

• The change in the degree of IS outsourcing differs between outsourcing and non-

outsourcing firms with respect to the following:

• Gaps in information quality, IS support quality, and IS cost of effectives and

• The condition of these gaps (high deprivation versus equilibrium or moderate

deprivation);

• The change in the degree of outsourcing;

• The degree of outsourcing success is related to the change in the degree of

outsourcing of specific types of IS functions. For example, outsourcing success is

highly related to changes in the degree of outsourcing of both systems operations

and telecommunication management and maintenance.

Jeanne Wenzel Ross and Kate M. Kaiser (1987)(18)

focused on End-User

Computing (EUC), which consumes a significant proportion of many organizational

computing budgets. The need to contain EUC costs as well as ensure effectiveness has led

many authors to recommend that top management or organizations device EUC

strategies. The goal of this study was to identify the factors related to EUC control and

not variances by industry. Data were collected through telephone interviews with a

marketing manager and as ISD manager in 87 organization in four industries. Analysis of

the data showed that IS control is positively related to four factors:

• Its ability to cope with EUC uncertainties,

• Its non-substitutability,

• The pervasiveness of the department’s data needs and

• The importance of EUC to the department coping with uncertainty.

The last factor has the greatest predictive power of the four variables. Data

pervasiveness proves insignificant in multiple regression equations. They proposed a

model by which ISD can gain EUC control.

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Chang Liu (1997)(19)

conducted a study to identify consumer reactions to a well

designed website. Four functions that are critical to the design of electronic markets were

identified; they are (1). Information and service quality (2). System use (3). Playfulness

and (4). System design quality. He identified that a well problems relating to difficulties

in integration have been explored. They made an attempt to identify difference in values

between information system professionals and non-information system professionals that

may be blocking integration efforts.

2.10 Information Support to People and Technnology

Lind, Marry Louise Robinson (2011)(20)

examined whether effective

communication between information systems personnel and non-information systems

personnel would result in greater information technology innovativeness. Two means

were proposed for achieving more effective information systems / organization

communication. (1). More frequent communication; and (2). The use of richer

communication channels. In the research model, two proposals were made. The level of

communication frequency and communication richness determines the level of

convergence: (convergence is the degree of mutual understanding between IS and the

non-IS personnel about the business activities performed in the firm’s departments) and

the importance of IT in supporting these business activities. More the conveyance, higher

the level of IT innovativeness.

Five periods of data collection were used in testing his research model, using

longitudinal casual research techniques. The following research results were obtained.

• Convergence between information systems personnel and non-information

systems personnel on the importance of the firm’s business activities and IT to

support them was found to be an important predictor of convergence.

• Communication richness is an important predictor of convergence.

• Communication frequency is not only an important predictor of convergence but

is an important predictor of communication richness as well.

Malcolm A. Mc. Nevin (1968)(21)

while reviewing Ackoff’s paper identified

reasons for the failure of information systems in marketing as i. The tremendous gap

between expectations of information systems people and ii. The state of the art in

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business today. He described how Coca-Cola Company was bridging the gap by setting

the management information system department at corporate level and carrying out

developmental research (to build new models) and continuing research (solving

predictable marketing problems).

Clavie Marnen Forrest (1984)(22)

described the design and implementation of a

Decision Support System (DSS) for marketing planning and control in a small, but

complex company and examined the nature of the difficulties encountered. An

intermediary with functional, rather than technical expertise is used in a strategy for

overcoming the problem. The findings of the research showed how the main focus of the

intermediary’s role needs to be adopted over the systems development cycle. From co-

ordination in design stages to system champion during the first part of the implementation

stage, and finally to a catalyst to ensure that the DSS is integrated into the decision-

making process. Two practical marketing exercises were undertaken to illustrate the

nature of the gap between the provision of information and its use. The lack of a formal

approach to planning and control is shown to have a significant effect on the way the DSS

is used and the role of the intermediary is extended successfully to accommodate this

factor. The conclusion was for the DSS to play a fully effective role, small firms may

need to introduce more structure into their marketing planning and that the role of the

intermediary, or information coordinator, should include responsibility for introducing

new techniques and ideas.

Charles D. Schewe and James L. Wiek (1997)(23)

suggested a marketing

approach to the successful design and implementation of management information

system. The study dawn the parallels between MIS Development function and marketing

function utilizing Taylor’s framework of marketing: marketing delineation, purchase,

motivation, product adjustment, physical distribution communications, transactions and

post transactions.

Donald R. Lehman (1970)(24)

attempted to sketch the elements of marketing

information system by starting with a “model of individual choice” and then developing a

system for evaluating marketing decision based on the model. Thus the key element in the

system becomes the individual choice model. They included evaluation of new products

and advertising effectiveness.

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2.11 Models foe Evaluation

Kamma Malik and D.P. Goyal (2000)(25)

attempted to understand the concept of

effectiveness and the application of different models for evaluating the information

system. An analysis of existing models, being used for measuring the effectiveness of IS

has also been made. An integrated model has been suggested that comprehends the

effectiveness of organizational IS with respect to product, process and environment

effectiveness. The findings in this paper would provide a basic material for furthering the

research in this area and also would provide the right directions for the corporate to carry

out the evaluation process of their information system.

W.H. Delone and Mc Lean (1992)(26)

identified the possibility of two types of

measures in IS evaluation, viz., qualitative and quantitative. They developed a

quantitative IT utility index to quantity measures of effectiveness.

Eldon Y. Li (1997)(27)

summarized IS success factors into 8 categories and

further sub categories as given below:

i. System Quality: Response time, conveyance of access programming, language

features used, security, realization of user needs, documentation, flexibility, and

integration of systems.

ii. Information Quality: Accuracy, timeliness, precision reliability, currency,

completeness, format, clarity and instructiveness.

iii. Information use: Volume of output.

iv. User satisfaction: Top management involvement, charge back method of

payments for service, user’s participation, user’s confidence and support of

productivity tools.

v. Individual impact: User’s expectation of IS support, job effect of IS support,

perceived utility.

vi. Service Quality: Technical competence, attitude of staff, scheduling of CBIS

products and services, time required for system development, processing of

change requests, maintenance support, means of I/S, user’s understanding of

systems and training of users.

vii. Conflict resolution: Competition between CBIS and non-CBIS units, allocation

priorities for CBIS resources users and CBIS staff relations and communication,

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personal control over CBIS, organizational position of CBIS unit and user’s

attitude towards CBIS.

viii. Organizational Impact: Productivity improved by CBIS, efficiency of systems and

effectiveness of the systems.

Time Saarimen (1996)(28)

recommended four measurement scales for IS success

model as stated below.

� Development process (Cost and Efficiency use)

� Use process (User Satisfaction)

� IS product quality (performance Efficiency)

� Impact of IS on organization (Benefits)

The emphasis is both on process and product evaluations.

P.G. Kulkarni (1997)(29)

suggested the use of IT utility index to measure the

effectiveness of IT in banking. The measures are as follows:

� Technology costs as a percentage of the total operating cost.

� Transaction processing costs.

� Technology led exposures and risks.

� System availability indicators.

� Technology awareness of the knowledge works.

� Customer friendliness, flexibility and innovativeness of the system.

The study suggested that similar index parameters can be developed for other

industries also.

Erik Brynjolfson (1996)(30)

suggested three approaches to IT value estimation.

� Output and productivity estimation.

� Business performance. Various business metrics are profits, sales, market share,

growth, stock price appreciation etc.,

� Consumer surplus from derived demand.

James W. Reihl (1995)(31)

identified three major questions that companies keep

on asking and try to answer as:

� Are we selecting and funding the right IT project?

� Are we getting our money’s worth?

� Do our measurements tell us how well are we achieving the goal?

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The answer to these can be found in the effectiveness of IS. ‘IS’ is said to be

effective if its product is effective. The product of IS can be termed as effective if they:

� Provide quality information as per the user’s perception.

� Improve management function.

� Improve resource utilization.

James W. Cordata (1998)(32)

recommended the use of Balnidge criteria for

getting the snapshot of IS effectiveness. Balnidge criteria have seven categories defined

for any quality assessment. They are leadership, information and analysis, strategic

planning, HRD and HRM, process management, business results and customer

satisfaction.

Glenn Edward Maples (1997)(33)

examined service quality is a component of

overall information systems quality. He tested three related studies of SERVQUAL. He

found that SERVPERF’ outperformed SERVQUAL in all three studies.

Miller, Marc Donald and Rainer, R. Kelly Jr. (1994)(34)

extensively examined

the success or failure of IS. Success variables were proposed. They attempted to examine

the perceived ease of use and usefulness of the IS as a means to predict its use. The

Technology Acceptance Model (TAM) assumes complete volition control over the IS or

technology in question. Volitional control, therefore the TAM may not be able to predict

use in these situations. They had proposed and tested the Extended Technology

Acceptance Model (ETAM). This model was designed to predict usage behaviours where

volitional control over using the technology was absent. They concluded that ETAM

model significantly explains more variance in IT usage behaviours than the TAM, and

also indicates that the active participation change strategy gives the user optional control

over the technology, while the persuasive communication change strategy does not.

Karahanna, Elena and Detmar W Straub Normal L. Chervany, (1993)(35)

Identified that though organizations adopt information technology to support knowledge

workers, many users were unwilling to use available systems, and thus, the full benefits

of IT are often not realized. Guided by a theoretical model derived by combining

innovation diffusion theory of reasoned action to contribute to a better theoretical

understanding of the antecedents of user acceptance and user resistance to the adoption of

information technology, they carried out their study and found that:

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• Potential adopters base their adoption decisions on a sparser set of innovation

characteristics than suggested by the innovation diffusion literature;

• Users and potential adopters differ on their determinants of behaviour intention

and attitude, and

• There are significant differences between low and high innovativeness and users

in the determinants of subjective norm and behavioural interim.

James Edward Turner Julian W. Riehl (1993)(36)

proposed a model to analyze

the influence of factors related to use and satisfaction with information systems. The more

satisfied firms follow a plan for system development, have top management interest in IS,

provide periodic technology updates for management and users, and use prototypes to

speed development. Firms with more experience with scanning were more satisfied with

IS support while firms with more computer experience rated IS support lower. Advanced

communication technologies were used by the more successful firms including central

processing of sales data and Electronic Data Interchange (EDI).

Bernadettee Agatha Szajan (1990)(37)

suggested that user’s attitude towards a

proposed information system would provide system developers with some knowledge of

the potential success or failure of that information system.

Ginzberg (1981) and Dasantis (1983)(38)

suggested the importance of

investigating user’s expectations of information systems particularly the effects of

realistic expectations. Their research investigated user expectation system and the

consequences of realistic versus unrealistic expectations. These treatment groups

consisting of subjects with user expectations made up the independent variable. After

using an information system to make decisions, the dependant variables of user

satisfaction, perceived decision performance and system usage were measured to detect

the effects of differing levels of expectations on system effectiveness. Their finding in

this experiment suggest that pre-implementation expectations have an effect on user

satisfaction and perceived decision performance. No effect was found for either decision

performance or IS usage. The results are consistent with the predictions of cognitive

dissonance theory-those users with unrealistically high expectations and perceptions of

the information system that were higher than those with moderate expectations and those

users with unrealistically low expectation had significantly lower perceptions. Even after

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repeated uses of the information system, significant differences were found among the

three expectation groups although the trend indicated a moderating of the high and low

expectations groups both in their perceptions and post implementation expectations.

Allan Fletecher Gillman (1995)(39)

tried to develop a comprehensive

examination of the influence of Electronic Data Interchange (EDI) on marketing channels

of distribution. The study derived some propositions that are loosely organized for

structural outcomes, efficiency outcome, or strategic outcomes and examined three

different industry groups such as telecommunications, information systems and food

retailing. The study found no support for the structural outcomes, partial support for the

efficiency outcomes, and strong support for the strategic outcomes and the role of EDI in

promoting electronic commerce in marketing channels of distribution is a complex and

interesting one. As a new medium for information transfer it simultaneously expands and

adds value to inter organizational communications. What it does is shift the emphasis in

channel theory from a structural to a more strategic orientation.

Vijaya Sarathy, Leo Ramesh, and Daniel Robey (1994)(40)

examined the

consequences of Electronic Data Interchange (EDI) use on Inter-organizational Relations

(IR) in the retail industry. EDI is a type of Inter-organizational Information System that

facilitates the exchange of business documents in structure, machine processable form.

The model links EDI use and three IR dimension-structural behavioural and outcome.

The study proposed 14 hypotheses and tested them by using multiple regression analysis.

The analysis supports the following hypothesis.

• EDI use is positively related to information intensity and formalization.

• Formalization is positively related to cooperation.

• Information intensity is positively related to cooperation.

• Conflict is negatively related to performance and satisfaction.

• Cooperation is positively related to performance; and

• Performance is positively related to satisfaction.

Philips Kotler defines(41)

“A marketing information system is an interacting and

long-lasting structure of people, actions and tools to sort, evaluate, and distribute

pertinent, accurately and timely information for use by marketing decision making to

improve their marketing planning, execution, and control”. Cox and Good (1976) gave

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primary definition of MKIS who described MKIS as a set of methods and procedures for

effective planning, execution and demonstrating information needed in taking marketing-

related decisions. The concept of Marketing Information System is designed to meet the

unique needs of an individual organization. The requirements of MKIS will vary and

depends on the size and complexity of operations. For example, Systems that are suitable

for community sized institutions will not necessarily be adequate for larger organizations.

However, basic information needs and requirements are similar in all organizations

regardless it’s size. The complexity of operations, and / (or) activities, together with

organization size, point to need or the MKIS of varying degrees of to support the decision

making processes. Numbers of potential studies have attempted to assess the effectiveness

of Information System (IS), especially in the general IS field. The majority of research

on the IS effectiveness is limited to the financial indices measurement, such as ROI,

ROA, etc (Qing and Plant, 2001, Krishnan and Sriram, 2000, Ryan and Harison, 2000,

Thatcher and Oliver 2001), the market share and the cost study (Gurbaxani and

Mendelson, 1990, Railing and Housel, 1990), the productivity analysis (Qing and Plant,

2001, Hitt et al., 2002, Grover et al., 1998), the profitability (King 1998, Hitt and

Brynjolfsson, 1996).

According to Grover et al., (1996) (42)

, all the studies of IS effectiveness could be

classified into four groups: a) Criteria demonstration research, b) Measurement research,

c) Criteria relationship research, d) Antecedents of IS Effectiveness research. The first

group includes criteria demonstration studies, namely the theoretical development and

justification of effectiveness criteria, which are mainly financially oriented (e.g. Matlin

1979, Money et al., 1988). The second group is comprised of studies aiming at

statistically developing and evaluating measures for assessing the IS effectiveness (e.g.

Baroudi et al., 1986, Davis, 1989, Galeta and Lederer 1989), while the third group is the

composition of studies that attempts a linking between theory and statistical evaluation of

various instruments employed for assessing the IS effectiveness (Ein-Dor et al., 1981,

Sabherwal and Kirs 1994). Finally, the fourth group is comprised of studies that focus on

the antecedents of the company’s IS effectiveness (e.g. Montazemi 1988, Raymond

1990). Interestingly enough, an extensive examination of subsequent studies in IS

effectiveness shows that the four pillars identified by Grover et al., (1996) remain as the

dominant logic of scholar inquiry on effectiveness. For instance, the work of Qing and

Plant (2001) as well as of Krishnan and Sriram (2000) take a financial perspective on IS

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effectiveness. The studies by Dishaw and Strong (1999), Mahmood and Mann (2000),

and Jiang et al., (2002) focus on developing financial measures for assessing IS

effectiveness, whereas Jiang et al., (2001), and Negash et al., (2003) attempted to link the

development of specific measures with the underline theory on effectiveness. Finally,

Ragowsky et al., (2000), Tallon et al., (2000), and Heo and Han (2003) attempted to

investigate the antecedents and the consequences of the IS effectiveness.

Noori and Hossein (2005) (43)

projected a new decision-support-system (DSS) a

framework of marketing in the B-2-B (Business-to-Business) arena based on customer-

relationship management (CRM) and knowledge-driven marketing decision support

system to help related-field graduate students and marketing managers.

Jayachandran & Vardaraja (2006)(44)

argues that firms requires information

support to gain a competitive edge in order to survive and grow.

Michael J. Valos and David (2007)(45)

investigated the pressure of Porter’s

strategy types on the use of customer relationship management (CRM) techniques and

established market research for enhancing strategic decision making, increasing usability

of obtainable data, presenting plans to senior management, and achieving efficiency,

production and economical outcomes.

Grozdanovic, and K Larmann (2007)(46)

argue that maintaining and enhancing a

firm’s responsiveness to environmental changes may create a competitive advantage and

thereby enhance a firm’s financial performance. Failure to response to customers and

competitors could waste a firm’s scarce resources.

S. Afr. J. Ind. Eng. & Pretoria (Aug. 2012)(47)

study explains that the data

acquisition and IT infrastructure strongly support the information process. Information

processing significantly and positively predicts both service quality and business

function. But the business function that uses processed data and information for its

activities – such as planning, decision – making, and implementation – is not found to be

a significant predictor of service quality.

Nastaran Heydari, Reza Shafeai, Fereydon Ahmadi (2012)(48)

study examined

that Marketing Information System (MKIS) has a direct and meaningful relation with all

aspects of market efficiency variable. From effectiveness viewpoint, marketing

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information system has the most effect on customer satisfaction. Variables of cost

decrease, sales increase and market share are influenced by marketing information system

respectively.

Rahul Hakhu, Ravi Kiran and D.P. Goyal (2013)(49)

Investigated the role of

Marketing Information System (MKIS) for organizational culture and its effectiveness.

This study investigated the success factors of MKIS depends largely on the

organizational, technical, managerial and technical cultures / environments of a company.

These cultures are to be nurtured and made developed in order to improve and install a

sustainable MKIS for accomplishing the corporate objectives in the highly competitive

world economy in the long run.

Bashar A Ikhawaldeh. &, Ayed Al Muala (2013)(50)

aimed to identify the

impact of the antecedents of banking performance in the banking sector in Jordan

Population. This study consists of bank marketing managers in Jordanian banks, the

population sizes of banks used in this study are 150 marketing executives. Results of this

study showed that all antecedent of banks performance. Attitude, ease of use, usefulness,

market procedures, employee support, customer’s knowledge and market responsiveness

have positive and significant influence on banks performance.

Nevertheless, despite the fact that the IS effectiveness has become the object of

many empirical researches; it remains still one of the most important “unknown” issues in

the literature. A possible explanation for this may be the lack of an empirically derived,

reliable and integrated measure for assessing the effectiveness of IS. In fact, while most

of the studies focus on assessing the effectiveness of the company’s Management

Information Systems (MIS), its Decision Support System (DSS) or its Executive

Information Systems (EIS), no particular attention has been drawn on the Marketing

Information System (MKIS) and its effectiveness.

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2.12 A Bird’s Eye view

A brief presentation of the review of literature is depicted in Tables 2.1 to 2.4

Table 2.1: Concept and Components of MKIS

S.

No Researcher Year Findings

1. Seymour Banks 1968 System concept was being used by a minority of

even the largest firms. Companies using the system

concept in marketing show a wide range in its

implementation. The most companies operating

only sub-system application.

2. Kenneth P. UHL 1968 Marketing information system components are

i. Selective Dissemination Sub-System (SDS)

ii. Retrospective Research Sub-System (RSS)

iii. Unsolicited Information Sub-Systems (UIS)

3. John M. Mc Cann 1986 A new marketing discipline “marketing

informatics” was proposed. The term was designed

to describe the integration of traditional marketing

information systems with a range of new

information technologies as well as information

management procedures. Gave frame work for

marketing expert system.

4. Raymond R. Bruke 1994 Identified new technologies that can further the

development of artificial intelligence (AI) systems

for both everyday and strategic decisions. He briefly

described ADCAD system.

5. Hotaka Katahira

and Shigeru Yagi

1994 Described the state-of-the-art Point of Sale

Marketing Systems in Japan. Illustrated how

different market conditions across cultures lend to

the use of essentially the same technology in

somewhat different ways.

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Table 2.2: Importance of MKIS

S.

No Researcher Year Findings

1. Van Engelen, and

Johannes Marrie

Lucien

1989 Compared the usual dyadic models. An

empirical study conducted and proved that

the hypothesized relation between a

marketing strategy and the information

system with regard to the success of the

product market combination.

2. David Ing and Andrew

A. MitcheIL

1993 Described different sources of electronic POS

(Point of Sale) data, and discussed a typology

of decisions for which electronic POS data

are best suited for marketing decision.

3. John Deighton, Don

Peppers, and Maritha

Poggers

1994 Reviewed the power and potential of

customer databases. Suggested ‘interactive’

marketing in the place of ‘broadcast’

marketing. There is a necessity to marry

“high-powered analytical tools” with

specialized interactive marketing

communication techniques.

4. George Day and Rashi

Glazer

1994 Opined that, the feasible organization

changes that can overcome impediments and

ensure competitive advantage can be realized

from investment in information systems.

5. Bannie K. Buckland

James C. Bancheau

1995 Important variables of MKIS are of

perceived contribution of IT to the firm,

number of sources from which computer

education and training were received, firm

size, user involvement, years of in house

Information Systems (IS) experience,

computer knowledge in the firm, and

perceived availability of technical support.

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Table 2.2 Continued

S.

No Researcher Year Findings

6. Richard B. Rosecky 1986 This research shows that an existing

information gathering system, i.e.,

registration cards, can be used to reduce

information delays experienced by producers

and hence reduce the effects of some

marketing dysfunctions.

7. Edvard Philip Bovich 1987 Examined the relationship between marketing

management decision-making process and

decision quality and usage of computerized

decision support system. Results suggest that

usage of the decision support system have its

most direct benefits.

8. Gaillynn Cook 1990 The results indicated that sharing marketing

feedback, feedback and decision models, or

data and decision models increased

coordinated decision making above the

control level.

9. Jiro Kokuryo 1992 Describes how information technology

triggers the reorganization of logistics

systems specifically, explains EDI based

Quick Response (QR) systems being

implemented.

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Table 2.3: Development of MKIS

S.

No Researcher Year Findings

1. Donald F. Cox and

Robert E. Good

1967 Presented current “State of thought” and

identified some of the key decisions which

must be made by top management in the MIS

development process.

2. Robert C. Blatiberg and

Byong-do kim and

Jiangming Ye

1990 Evolved frameworks for “Mass produced”.

They described a typical application of

MDSS development of a price simulator for

setting retail prices across many items in a

product category.

3. Cheon, Myunjoong and

Grover, Varun; Tegn,

James

1992 A contingency model of out-sourcing was

developed from the literature. Two

hypotheses were developed.

� Organizational attributes influence the

change in the extent of an

organization’s outsourcing of ‘IS’

functions.

� Success of outsourcing is dependent

upon both the change in degree of ‘IS’

outsourcing and the quality of

outsourcing implementation.

4. Somendra Pant and

HSU Cheng

1997 Reviewed the business use of internet

technology and identified the lack of stable

models. He proposed a ‘push’ model for

internet strategy planning. Additional case

studies were taken from literature and

usefulness of reference model and planning

frame work were established.

5. Gernot Bernhand

Langle

1998 Found that presence of function specific

domain knowledge affected the construction

of representation as well as modeling,

discovery and validation process.

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Table 2.3 Continued

Sl.

No Researcher Year Findings

6. Ross, Jeanne Wenzel

Ross and

Kate M. Kaiser

1987 Conducted a study with the goal of

identifying the factors related to EUC control

and noted variables in the industry.

7. Change Liu 1997 Four functions that are critical to the design

of electronic markets were identified, they are

1. Information and service quality

2. System use

3. Playfulness and

4. System design quality

The study identified that a well

designed website will increase the level of

customer recall and recognition.

8. Ray joseph

Blankenship James H.

Barnes Jr. and

John D. Hohnson

1994 The study explored modeling of consumer

choice. They found that the GANNT

algorithm is able to significantly predict

better than the back propagation algorithm

and the predicted multi-nominal legit model.

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Table 2.4: Evaluation of MKIS

S.

No Researcher Year Findings

1. Nature of Function

1. Ackoff 1966 According to Ackoff systems development

has not been successful because: first,

marketing decision is increasing in

complexity at an accelerating pace. Second,

marketing decisions, as a class are more

difficult to model than other business

decisions. Third, many of the methods that

have been developed for modeling these

decisions are inadequate when checked with

real world results.

2. IS and User Conflict (Interpretation)

1. Richard H. Brien 1968 There is a clear need for a very special kind

of intermediary between systems ‘users’ and

system technicians. He found in one company

two new positions. Information systems

manager and operations research manager

were crated before acquisition of a larger,

more sophisticated computer system and it

was successful.

2. Dickson Warren lee

and Leon R. Price

1994 Identified a variety of problems that prevent

IS professionals and Non-IS professionals

from joint realization of the system.

Individual differences, social differences and

interaction (communication) problems

relating to difficulties in integration have

been explored.

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S.

No Researcher Year Findings

IS People & Technology

1. Linkd, Mary Louise

Robinson

1988 Convergence between information systems

personnel and non-information systems

personnel on the importance of the firm

business activities and IT to support them

was found to be an important predictor of IT

innovativeness. Communication richness is

an important predictor of convergence.

Communication frequency is not only an

important predict of convergence but is an

important predictor of communication

richness as well.

2. Malcolm A. Mc. Nevin 1968 A reason for the failure of information

systems in marketing is tremendous gap

between expectations of information systems

people and the state of the art in business

today. He described how Coco-Cola

company is bringing the gap by setting the

management information system.

3. Claire Maureen, Forrest 1984 DSS to play effective role, small firms may

need to introduce more structure into their

marketing planning and that the role of the

intermediary as such include responsibility

for introducing new techniques and ideas.

4. Charles D. Schews and

James I. Wiek

1977 They have drawn parallels between MIS

development function and marketing function

utilizing Tailor’s framework of marketing

delineation, purchase motivation, product

adjustment, physical distribution

communications, transactions and post

transactions.

Table 2.4 Continued

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S.

No Researcher Year Findings

5. Donald R. Lehman 1970 Sketched the elements of marketing

information system by starting with a model

of individual choice and then developing a

system for evaluating marketing decision

based on the model. The several applications

of this system seem feasible. They include

evaluation of new products, advertising

effectiveness and product aging.

4. Models of Evaluation MKIS effectiveness

1. Kamma Malik and DP

Goyal

2000 An analysis of existing models, being used

for measuring the effectiveness of IS has also

been made. An integrated model has been

suggested that comprehend the effectiveness

of organizational IS with respect to product

process and environment effectiveness.

2. W. H. Delone and Mc.

Lean

1992 Identified the possibility of two types of

measures IS evaluation, viz., qualitative and

quantitative developed.

3. Eldon Y. Li 1997 Summarizes IS success factors into 8

categories and further sub categories as:

i. System gravity,

ii. Information gravity,

iii.Information use,

iv.User satisfaction,

v. Individual impact,

vi.Service quality,

vii. Conflict resolution and

viii. Organizational impact.

Table 2.4 Continued

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S.

No Researcher Year Findings

4. Timo Saarimen 1996 Recommends four measurement scales for IS

success model, as stated.

� Development process (Cost and

efficiency use)

� Use process (User satisfaction)

� IS product quality (Performance

efficiency)

� Impact of IS on organization (Benefits)

The emphasis is on both process and product

evaluations.

5. P.G. Kulkarni 1997 Suggested the use of IT utility index to

measure the effectiveness of IT in banking.

They are as follows.

� Technology costs as a percentage of the

total operating cost.

� Transaction processing costs.

� Technology led exposures and risks.

� System availability indicators.

� Technology awareness of the

knowledge works.

� Customer friendliness, flexibility and

innovativeness of the system.

Similar index parameters can be developed

for other industries also.

6. Erick Brynjolison 1996 Suggests three approaches to IT value

estimation.

� Output and productivity estimation.

Output = 1 (computers, labour, capital

etc.,)

� Business performance metrics = 1

(Computers, environment, strategy etc.,)

� Various business metrics – profits, sales

market share, growth, stock price

appreciation etc.,

� Consumer surplus from derived

demand.

Table 2.4 Continued

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S.

No Researcher Year Findings

7. James W. Cortada 1995 Information system is said to be effective if

its product is effective. The product of IS can

be termed as effective if they:

� Provide quality information as per the

user’s perception.

� Improve management function.

� Improve resource utilization.

8. James W. Cortada 1998 Recommended the use of Balnidge Award

criteria for getting the snapshot of IS

effectiveness. Balnidge criteria have seven

categories defined for any quality assessment.

They are leadership, information and

analysis, strategic planning, HRD and HRM,

process management, business results and

customer satisfaction.

9. Glenn Edward Maples 1997 Service component of information systems

yields better results than SERVQUAL AND

SERVPERF instruments.

10. Miller, Marc Donald

and Kelley R. Rainer

Jr.

1994 Proposed user satisfaction as a success

variable. They found that the Technology

Acceptance Model (TAM) may not be able to

predict use in these situations. They had

proposed and tested the Extended

Technology performance; and Acceptance

Model (ETAM).

11. Karahanna, Elena and

Detmar W, Straub and

Chervany, Norman L

1993 Identified that the organizations adopt

information technology to support knowledge

workers. Yet many users are unwilling to use

available systems, and thus, the full benefits,

Table 2.4 Continued

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of IT are often not realized. Guided by a

theoretical model derived by combining

innovation diffusion theory with the theory of

reasoned action to contribute to a better

theoretical understanding of the antecedents

of user acceptance and use resistance to the

adoption of information technology, they

carried out their study and formed that

a. Potential adopters base their adoption

decisions on a sparser set of innovation

characteristics than suggested by the

innovation diffusion literature;

b. Users and potential adopters differ on

their determinations of behaviour

intention and attitude and

c. There are significant differences between

low and high innovativeness and users in

the determinants of subjective norm and

behavioural interim.

12. James Edward Turner

and Julian W. Riehl

1993 Proposed a model to analyze the influence of

factors related to use and satisfaction with

information systems. The more satisfied

firms follow a plan for system development,

has top management interest in IS, provide

periodic technology updates for management

and users and use prototypes to speed

development. Firms with more experience

with scanning are more satisfied with IS

support while firms more computer

experience rate IS support lower.

13. Bernadettee Agatha

Szajna

1990 Suggested that user’s attitude towards a

proposed information system would provide

system developers with some knowledge of

the potential success or failure of the

Table 2.4 Continued

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information system.

S.

No Researcher Year Findings

14.Ginzberg & Desantis 1981

&

1983

Pre-implementation expectations have an

effect on user satisfaction and perceived

decision performance. No effect was found

on either decision performance or IS usage.

The results are consistent with the predictions

and perceptions of the information system

that were higher than these with moderate

expectations and those users with

unrealistically low expectations and those

users with unrealistically low expectation had

significantly lower perceptions. Even after

repeated use of the information significant

difference was found among the three

expectation groups although the trend

indicated a moderating of the high and low

expectations groups both in their perceptions

and post implementation expectations.

15.Allan Fletcher Gillman 1995 The role of Electronic Data Interchange

(EDI) in promoting electronic commerce

marketing channels of distribution is a

complex and interesting one. As a new

medium for information transfer it

simultaneously expands and adds value to

inter organizational communications. What it

does is shift the emphasis in channel theory

from a structural to emphasize more strategic

orientations.

Table 2.4 Continued

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S.

No Researcher Year Findings

16. Vijaya Sarathy, Leo

Ramesh and Daniel

Robey.

1994 The analysis supports the following

hypotheses.

� EDI use is positively related to

information intensity and formalization.

� Formalization is positively related to

cooperation.

� Information intensity is positively

related to co-operation.

� Conflict is negatively related to

performance and satisfaction.

� Cooperation is positively related to

performance; and

� Performance is positively related to

satisfaction.

2.13 RESEARCH FRAMEWORK

According to Okazaki (2005) branding strategy, location-based services, and

service costs were determined as the most important managerial factors in establishing

business models, while facilitating conditional, regulatory control, and cultural barriers

were the most relevant environmental factors for such models. However, this study

incorporated a variable “ease of use” model of the Technology Acceptance Model (TAM)

as part of the theoretical foundation for the development of the theoretical framework.

This shall assist in measuring the satisfaction of the MKIS. TAM posits that perceived

usefulness and perceived ease of use determine a person’s behaviour while applying and

using an accepted technology. The applicability of an extended version of the TAM was

tested by Wang et al. (2003) in Taiwan. Probing those factors that lead to behavioural

intention, the authors found evidence that perceived ease of use, perceived usefulness,

and perceived credibility all had a significant positive effect on people’s intention to use

an information system. There are four models that are used to measure the effectiveness

of MKIS, these are: Internal Process Model, Human relations Model, Open System

Table 2.4 Continued

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Model (OSM) and Rational Goal Model (RGM). These models are used in measuring the

performance of an organization using the effectiveness of MKIS. Conceptualization of the

MKIS effectiveness must be developed into a measuring instrument for experimental

application for data collection. Gounaris et al (2007) study combined the important four

models to measure the effectiveness of MKIS in organization. The instrument developed

by Gounaris et al (2007), is capable of revealing the effectiveness of the MKIS in an

organization in both internal and external components, relating to the extent to which the

user organization improves functional effectiveness and corporate climate and on the

other hand to its adaptability to market conditions and its customer responsiveness. The

authors inferred that a validated measure of the effectiveness of MKIS has important

implications for both users and providers. The validated instrument conceptually permits

improved understanding of the components of effectiveness. Pragmatically, the

instrument provides an assessment of the effectiveness of existing systems.

The Competing Values Model (CVM) appears to be a particularly attractive

framework for assessing the effectiveness of the company’s MKIS. It is based upon the

nation that “effectiveness” is a construct which is composed by a number of partial

meanings such as the efficiency, the productivity, the information management, the

flexibility, etc (Cameron, 1978).

Following the CVM (1983), a company can be placed along three axes:

a). Focus, b). Structure, and c). means-ends (Figure 1). These three dimensions allow the

definition of four basic models regarding the priorities pursued by the company; the

Human Relations Model, the Open System Model, the Internal Process Model and the

Rational Goal Model.

According to the CVM, effectiveness, at the macro-level, is associated with well

performance on all four models-priorities (Quinn and Rohrbough 1983).

The selection of CVM for the MKIS effectiveness measurement is adopted in the

present study since the said model is integrated and totally comprising all the types of

measurement valid in the literature, according to the theoretical model of Grover et al.,

(1996) (Figure 2.1).

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Figure 2.1: CVM with all Evaluation types in the Literature

�

This is because it includes a). Indicators of effectiveness with regard to the

process, and more specifically to the effectiveness of the information management, the

internal communication, etc. (Internal Process Model ~ Infusion Measures), b). Indicators

of effectiveness regarding the response the enterprise encounters from both its human

resources (Human Relation Model ~ Market Measures) and, finally c). Indicators with

regard to the effect the MKIS has no economical magnitudes, such as productivity,

efficiency, etc. (Rational Goal Model ~ Economics Measures).

2.14. Research Gap

From the above Literature Review it can be concluded that marketing decision is

increasing in complexity at an accelerating pace. Marketing decision, as a class is more

difficult to model than other business decisions. Many of the methods that have been

developed for modeling the marketing decisions and are inadequate when checked with

real world results.

2.15. Research Problem

Since the marketing is more than selling and promoting, marketing information

system is useful for the Financial Services Industry, especially large ones in-order to get

the firm to higher ranks. So the research problem is finding whether financial services

companies in India are using MKIS effectively not.

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2.16 Objectives of the Study

1. Identifying the underlying dimensions of Marketing Information System.

2. To find the influence of Technical characteristics on Marketing Information

System.

3. To find influences of sector, Type of Company, Level of Management and

experience on MKIS usage.

2.17 Research Hypothesis

H1: The system quality, the information quality, the support service quality,

compatibility and flexibility of Information System have positive impact on the

MKIS effectiveness.

H2: Sector, Type of company, experience and Level of Management does not

influence the MKIS usage.

2.18 Research Methodology

Type of Research Method

The study explores that Marketing Information System in Indian Financial Service

Sector and its effectiveness in Banking, Insurance and other Financial Intermediaries. A

survey was conducted with the help of structured questionnaire. The study uses a

descriptive research method.

2.19 Design of Questionnaire

A study was carried out at Financial Services Industry in India. The questionnaire

is designed based on Functional and Technical aspects. The MKIS effectiveness scale is

implemented using CVM model of Saaksjarvi and Talvinen’s (1993), as well as ELAM

model and kotler’s Marketing Information System model.

Nevertheless, according to the suggestions of the executives who helped in the

development of the research instrument, the scales were enriched with items aiming to

capture the MKIS effectiveness in relation to dimensions of the marketing mix, such as

promotion, communication, pricing, etc. The scale included 38 items and the respondents

were asked to answer on a 7-point scale (1=”strongly disagree” to 7’=” strongly agree”).

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S.

No. Factor Source (or) Studied

1. MKIS control advertising and promotional budget. Vanbruggen et al,

2. MKIS helps to prepare annual operating plans Petty & Caccioppo

3. MKIS helps to implement approval plans and programs. Oing & plant

4. MKIS coordinate activities among functional groups. Vanbruggen et al,

5. MKIS helps to product differentiation. Hitt & Brynjolfsson

6. MKIS liaise with the advertising agency. Saaksjarvi & Talvenin

7. MKIS coordinates for effective new product launches. Robber R. Harmo

8. MKIS arrange production to Point of scale promotional

literature.

Fryans, Mellahi

9. MKIS recommends individual marketing research

projects.

Phikip kotler

10. MKIS helps direct control with distribution channels. Gronhaug & Kaufman

11. MKIS help to coordinate elimination of obsenlence

products.

Gronhaug & Kaufman

12. MKIS provides information to head quarters for decision

making.

Cecez-Kecmanvoic

13. MKIS helps in regularly analysis and report market

research data to managers.

Takvinen & Timo

14. MKIS helps to monitor results against planned

performance.

Takvinen & Timo &

sarrimen

15. MKIS helps to make projections of competing products

market share.

Seymour banks

16. MKIS assess market size. Seymour banks

17. MKIS prepare forecasts of company sales by market

segment.

Chenal, R.H., &

Morris

18. MKIS helps to estimate the company’s market share. Panigyrakis and

chatzipanagiotou

19. MKIS monitor environmental developments likely to

have an impact on product performance.

Panigyrakis and

chatzipanagiotou

20. MKIS analyse competitor activities. Saaksjarvi & Talvenin

21. MKIS helps to prepare annual sales forecasts. Saaksjarvi & Talvenin

22. MKIS helps to the organization in marketing data

analysis.

Saaksjarvi & Talvenin

23. MKIS helps to prepare long term forecasts of industry

sales.

Saaksjarvi & Talvenin

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S.

No. Factor Source (or) Studied

24. MKIS employ portfolio analysis in assessing

performance.

Brown & Dacin

25. MKIS develops long term strategic marketing plan. Gronhaug & Kaufman

26. MKIS determine value of future income streams. Qing & Plant

27. MKIS helps your organization in selection of advertising

and promotional agency.

Petty & Caccioppo

28. MKIS helps to your firm for selection of distribution

channels.

Panigyrakis and

chatzipanagiotou

29. MKIS suggests allocation of promotional budgets. Panigyrakis and

chatzipanagiotou

30. MKIS Initiates product developments / modifications. Colgate

31. MKIS recommend the addition (or) deletion of products. Panigyrakis and

chatzipanagiotou

32. MKIS helps product design. Colgate;2000

33. MKIS establish brand performance criteria. Colgate ; 2000

34. MKIS evaluates promotional activities. Saaksjavri& Takvenin

35. MKIS assess product performance analysis. Saaksjavri & Takvenin

36. MKIS helps in providing customer service levels. Saaksjavri & Takvenin

37. MKIS helps to find the training needs of the marketing

employees

Saaksjavri & Takvenin

38. MKIS improves internal communication. Yolande E.chan

39. MKIS meets information requirements of user

anticipation.

Farnoosh khadarkhan

40. MKIS provides friendly working environment. Farnoosh khadarkhan

41. MKIS provides accurate data. Limkd,mary Louise

Robinson

42. MKIS processing speed is high Limkd,mary Louise

Robinson

43. MKIS provides information at right time. Clairre Maureen,

forrest

44. MKIS can be easily used Donald R.Lehman

45. MKIS uses latest s/w Limkd,mary Louise

Robinson

46. MKIS uses latest h/w Limkd,mary Louise

Robinson

47. MKIS is performing good during the services process Camron

48. Quality of information provided during service is good. Kamma malik and

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S.

No. Factor Source (or) Studied

D.P. Goyal

49. MKIS is enhancing Potential quality of organization Eldon Y Li

50. MKIS is helping organization to become success with

Immediate outcomes

Timmo sarrimen

51. MKIS is demanding customer solutions with quality Timmo sarrimen

52. MKIS is compatible with organization Transaction

processing system

James W. Cortada

53. MKIS is compatible with organization Management

Information System

Panigyrakis and

chatzipanagiotou

54. MKIS is a compatible with organization Decision

Support System

Panigyrakis and

chatzipanagiotou

55. MKIS is flexible to change Panigyrakis and

chatzipanagiotou

56. MKIS is portable to any environment Panigyrakis and

chatzipanagiotou

�

The Items include Coordination with implementation of organizational programs

11 items, Market Analysis and forecast 3 items, Projection of Market Size of

organization 8 items, Good Long term Strategies 7 items, Improvement to Product 3

items, MKIS Evaluation and control 4 Items and Identifying of Training needs for

marketing executives 2 items.

2.20 Population

Table 2.5: Distribution of Respondents in the Population

Category of Financial

Institutions

India wise

Branches

Karnataka

state wise

Tamil Nadu

state wise

Andhra

Pradesh

state wise

Banks 82349 5989 6144 6704

Insurance Company 18384 550 807 843

Other Financial

Institution 22264 200 255 270

There are 82,349 branches of banks, 18,384 Insurance offices and 22,264 financial

institutions. In total there are 1,23,087. As the population large in terms of cost, time and

employees involved, the investigator selected a sample of 15 banks, 15 insurance

companies and 15 other financial institutions covering from each state at least three

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Marketing Executive from each financial services company. Total sample institutions are

168.

2.21 Sampling Method

Table 2.6: Distribution of the Respondents in the Sample

Sector wise

Financial

Institutions

Karnataka

state wise

Respondent

institution

Tamil Nadu

state wise

respondent

institution

Andhra

Pradesh

State wise

respondent

institution

Respondent

institution

Respondent

Executives

Banks 06 25 40 71 213

Insurance

company 20 28 21

69 207

Other

Financial

Institutions

10 12 06 28

84

Total 168 504

The distribution of respondents is given in the Table 1.2.

In this study Survey method is implemented to collect the information from the

respondents and distributed to the Marketing executives in Financial Service industry.

The data has collected through mail survey and personal interview method which is

employed through Convenience Sampling.

2.22 Data Collection

A total of 672 questionnaires were distributed among Marketing Executives in

Financial service Industry. Out of these, 504 duly filled questionnaires were received.

The response rate is 75%. The highest response came from the Banking Industry

(42.36%), followed by Insurance Sector (41.07%) followed by other Financial Institutions

(16.67%).

2.23 Statistical methods used

Standard Deviation: Mean, Minimum, Maximum values and standard deviation were

calculated for different factors in different dimensions to the MKIS of Indian Financial

Service Sector.

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Factor Analysis: is a statistical method used to determine underlying variables of MKIS

effectiveness through factor analysis

Multiple Regression Analysis: In statistics, regression analysis is a statistical process

for estimating the relationships among variables. It includes many techniques for

modeling and analyzing several variables, when the focus is on the relationship between a

dependent variable and one or more independent variables. More specifically, regression

analysis helps one to understand how the typical value of the dependent variable (or

'Criterion Variable') changes when any one of the independent variables is varied, while

the other independent variables are held fixed.

2.24 Conceptual Frame Work: An analytical model representing system effectiveness

variables under study is shown in the following figure 2.2.

Technical Aspects

Functional

Effectiveness of

MKIS

Effective MKIS

System Quality

Information quality

Support Service

Quality

Compatibility

Flexibility

Co-ordination

with

implementation of

organizational

programs

Projection of

Market share

Market Analysis

& Forecast

Long term

Strategies

Product Analysis

MKIS evaluation

and control

Training needs of

Marketing

employees

Effective Economic

Decisions

Good Planning

Ease to perform

Market Analytics

Figure 2.2 Analytical Framework of Study

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2.25. Chapterisation

Chapter 1, presents an Introduction on Effectiveness of Marketing Information System in

the Indian Financial Service Sector.

Chapter 2, deals a Review of literature and establishes objectives and methodology for

the present study.

Chapter 3, Portrays evaluation of MKIS in Indian Financial Service Sector.

Chapter 4, Summarizes the Findings

Chapter 5, Provides Conclusions and suggestions for improving MKIS.

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50. Mualla ...... Bashar H. Malkawi; Haitham A. Haloush ...... MARKETING

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