Why hospitals also need benchmarking marketing capabilities? An empirical study of relationships between marketing practices and its outcomes.

Sharma, Anand ; Dadwal, Sumesh Singh ; Mahal, Sandeep Singh 等

Introduction

In dynamic competitive environment customer satisfaction is becoming the generic strategy of all marketers. Even hospitals and health care providers are feeling the heat of competition, particularly players in private sector. They are changing the ways of doing their business. But perhaps due to the prevalence of excess demand over supply the output of many public sector hospitals are not as per required quality standards. But now various forces of change, that include competitive pressures, alternate health care delivery mechanisms, changing cost structures, monitoring by public and private groups, increased information availability, and a markedly better-informed customer base, have begun to exert significant pressures on health care providers to reassess their strategic options. In order to obtain competitive advantage a health service providers (hospitals) should inculcate a market-based learning approach where they can identify and monitor value sources of competitive advantage, such as marketing capabilities, which can provide fact-based evidence to help managers recognize the need for capability improvements.

Profile of Health Industry in India

Health care industry is one of the fastest-growing industries in the service sector, which grew by more than 13 per cent per annum in the last decade. Highly qualified and experienced personnel man India's health services. Slowly, super-specialty hospitals specializing in both modern and traditional Indian medical systems supported by state-of-the-art equipment are now attracting patients from across the world. India's health care industry is estimated at Rs1,500 billion or USD 34 billion. In a country geographically widespread and having so much socioeconomic diversity no one can serve all. So segments of health care providers are emerging which are targeting specific socioeconomic or lifestyle segments. Private players are attracting high net-worth patients both from the domestic and the international market. The government is always under fiscal pressure and advises public sector units to improve efficiency or generate additional resources. Here lies the opportunity and threat in front of the so-called relaxing market players. There are more than 140 million upper- and middle-class population, growing at over 4 per cent per annum with combined annual income of over Rs820,000 crore. Further, privatization of the insurance sector has led to a spurt in health care services. Insurance is expected to be the main driver for raising quality consciousness and increased demand for better standards, hospital accreditation, and patient- management information systems.

Review of Literature

In the present work researchers have looked into marketing drivers and expectations of health care service providers in Chandigarh and its surrounding area. It has been recognized that market-based learning is an important source of sustainable competitive advantage (Hult 1998; Slater and Narver 1995). Barney, (1991) observed that four indicators, viz., value, rareness, inimitability, and non-substitutability, provide a firm the much required ability to generate sustained competitive advantage. Galbreath and Galvin (2004) discovered that while RBV (Recourse-based view) theory largely associates firm performance with intangible resources, the association might not always hold true empirically. One explanation may be that the strength of some resources are dependent upon interactions or combinations with other resources and therefore no single resource--intangible or otherwise--becomes the most important to firm performance (Academy of Management, Best Conference Paper, 2004 BPS: L6).

Strategic marketing scholars have identified a firm's market orientation as its ability to learn about its market environment and to use this knowledge to guide its actions appropriately (Hunt and Morgan 1995; Jaworski and Kohli 1993; Narver and Slater 1990). It has been found that relatively higher emphasis was placed on the marketing strategy by firms which are large, are involved in consumer goods industry, are involved in exports, have high domestic sales growth, and have adopted a differentiation strategy combined with a cost leadership strategy (Sharma 2004). But it has also been noted that the basic principles of marketing appear to be equally valuable to both large and small firms. (Wai-sum Siu and Kirby 1998). Literature has illustrated that each marketing capability is directly and positively related to firm performance, indicating that these marketing capabilities are sources of competitive advantage (Vorhies and Morgan 2005). Further they observed that marketing capability interdependency factor is strongly and positively linked with a firm's performance. This indicates that for designing customer service strategies these marketing capabilities should be of the utmost importance and a firm or a hospital should focus on these marketing variables to achieve a competitive advantage.

Need of the study and corresponding constructs

Thus, keeping the literature in mind this study was conducted to find out the basic strategies, which help hospitals to achieve a competitive advantage. Although numerous studies related to hospital have been conducted, no one specifically attempted to identify the underlying determinants of hospital profitability. If these factors are identified, hospital executives can focus their efforts on those aspects of operations that affect profitability most, and public policy makers can gain insights into the potential effects of alternative policy decisions on hospital financial viability. A study was conducted with twenty-two hypothesized profitability determinants as independent variables and five profitability measures as dependent variables. The results provide evidence that selected managerial and patient-mix variables are predictors of profitability. It appears profitability is not dictated by organizational or market factors but more strongly influenced by factors that, to some extent, can be influenced by hospital policies and practices (Gapenski, Vogel, and Langland-Orban 1993).

Based on previous literature review, in the current research, researchers have identified eight distinct marketing capabilities, which contribute to business performance (Vorhies and Morgan 2005). These marketing capabilities or the strategic elements which lead a firm to achieve competitive advantage are:

* Product Development, the process by which firms develop and manage product and service offerings (Dutta, Narasimhan, and Rajiv 1999);

* Pricing, the ability to extract the optimal revenue from the firm's customers (Dutta, Zbaracki, and Bergen 2003);

* Customer Management (a process by which a firm retains its customers and saves on making new customers which can lead to profitability), the firm's ability to establish and maintain Customer Relationship Management (CRM) that effectively and efficiently delivers value to consumer (Weitz and Jap 1995);

* Marketing Communications, the firm's ability to manage customer value perceptions (McKee et al. 1992);

* Staff management, the process by which the firm encounters customer orders (Shapiro, Slywotzky, and Doyle 1997);

* Market Information Management, the process by which firms learn about their markets and use market knowledge (Day 1994; Menon and Varadarajan 1992);

* Marketing Planning, the firm's ability to conceive marketing strategies that optimize the match between the firm's resources and its marketplace (Morgan et al. 2003);

* Marketing Implementation, the process by which intended marketing strategy is transformed into realized resource developments (Noble and Mokwa 1999). In the present research work market performance is measured with respect to market effectiveness and current profitability of hospitals.

Objectives of the Study

The study was conducted with a view to:

* Finding out the association between income group of patients and type of hospitals and marketing variables/drivers.

* Finding out the relationship between marketing drivers (Product Development, Pricing, Customer management, Marketing Communication Staff, Marketing Information Management, Marketing Planning, Marketing Implementation) and marketing outcome (Market Effectiveness and Current Profitability).

* Finding out the differences between marketing strategies of government and private hospitals.

Research Methodology

Data were collected from fifteen hospitals (all big hospitals) with the help of a well-structured questionnaire vide Annexure 1, which was submitted to marketing administrators of hospitals. For developing the questionnaire, the scale was adapted from an earlier paper, 'Bench Marking Capabilities for Sustainable Competitive Advantage' (Vorhies and Morgan 2005). The data collected were analysed by using statistical tools, viz., Chi-square test, Correlation test, Regression analysis and ANOVA, using Microsoft Excel and SPSS software.

Analysis of Data

Type of customers and type of hospitals

[H.sub.0]1 : There is no relationship between the type of hospital and the income group of the patients.

To find out the relationship between the income groups and the preference for the type of hospital, the Chi-square test was performed. From the Chi-square test the [chi square] (p = 0.000 at [alpha] of 0.05,) indicates that there may be some relationship. Further, as it may be observed from Table 1, certain frequencies are low so Yeats correction factor was applied which again lead's to rejection of the Hypothesis ([chi square] calculated = 5.63, [chi square] tabulated = 3.84).

Scores for marketing variables

Researchers observed that the means of score as given by marketing heads of hospitals (on Lickert scale) for the marketing variables/drivers are almost same, except for Marketing Communications, where the private hospitals pay more attention. Further, all scores are on the higher side on a scale of 1-7, most of the score being more than 5.

Marketing variables:

 Govt. Private

1. Pricing 5.72 5.59
2. Product Development 5.59 5.82
3. Customer Management 5.02 5.35
4. Marketing Communications 2.45 5.71
5. Staff Management 6.04 6.10
6. Marketing Information 3.88 3.77
 Management
7. Marketing Planning 3.48 4.20
8. Marketing, Implementation 4.95 5.23

For marketing planning and information management the scores are low. Higher score values indicate that hospitals deliberate upon strategies related to Pricing, Product Development, Customer Management and Staff. While other variables/drivers like Information Management, Planning, and Marketing Implementation are given lesser preference by both types of hospitals.

Further, the analysis reveals that hospitals generally try to formulate strategies specific to 'patient segments'. Hospitals catering to the higher income group (HIG) tend to focus marketing strategies on these drivers/variables and those catering to the lower income group (LIG) do it to a lesser extent.

Scores on marketing variables/drivers:

 LIG HIG

l. Pricing 5.7 6.0
2. Product Development 5.5 5.8
3. Customer Management 5.0 5.3
4. Marketing Communications 2.4 5.7
5. Staff 6.0 6.1
6. Marketing Information 2.8 3.7
 Management
7. Marketing Planning 3.4 4.2
8. Marketing Implementation 4.9 5.2

As already established with Chi-squire private hospitals mostly cater to higher income group of the society and government hospitals to lower income group. So it can be further inferred that private hospitals are using these market drivers more vigorously than government hospitals. This can be because private hospitals compete to gain the patients base, whereas government hospitals fight for social needs and they generally do not formulate strategies keeping in mind those of the competitors. Marketing Communications has a significant difference in the means, which might be because the patients of the higher income group want to know more about any hospital before going to it. Thus private hospitals or the hospitals which want to attract this segment have to communicate aggressively that patients believe in them. On the other hand government hospitals or those catering to the lower income segment of the society do not need to advertise much.

[H.sub.0]2 : There is no difference of scores of the 'strategic marketing variables' between government and private hospitals in Chandigarh.

To find out whether there is statistical difference of the scores of marketing drivers and to establish tentative relationship between a parametric (marketing variables/ drivers) and a non-parametric variable (type of hospital: government or private) researchers compared the means of scores using Independent Samples T Test, as follows:

[H.sub.0]2a : There is no difference in the pricing strategy of government and private hospitals.

T-test indicate that there is no significant difference between the Pricing Strategies of government and private hospitals (p = 0.535 at [alpha] of 0.05, mean difference = 0.352, and Levene's p = 0.771). There is no evidence to suggest that two means are different. Although private hospitals appear to focus more on pricing strategies than the government hospitals.

[H.sub.0]2b : There is no difference in the product development strategy of government and private hospitals.

Further, no significant difference in the product development strategy was found between the government and private hospitals (p = 0.392 at [alpha] of 0.05, mean difference = 0.257 and Levene's p= 0.432). There is no evidence to suggest that two means are different.

[H.sub.0]2c : There is no difference in the customer management strategy of government and private hospitals.

No significant difference in the customer management strategy was found between government and private hospitals (p = 0.613 at [alpha] of 0.05, mean difference = -0.3363 and Levene's p= 0.656). There is no evidence to suggest that two means are different.

[H.sub.0]2d : There is no difference in the marketing communication strategies of government and private hospitals.

Test rejects the null hypothesis that there is no difference in the marketing communication strategies of government and private hospitals (p = 0.000 at [alpha] of 0.05, mean difference = -3.3 and Levene's p = 0.706). There is no evidence to suggest that two means are different. From the mean scores, the researchers inferred that a difference lies in the focus on communication as driver of marketing between the government and private hospitals (mean score Government = 2.45, Private = 5.71). This shows that the private hospitals do take care of their corporate image and advertise themselves accordingly. A few private hospitals have websites of their own which are updated periodically whereas some big government hospitals also have websites which are not updated since long.

[H.sub.0]2e : There is no difference in the management of staff among government and private hospitals.

The null hypothesis that there is no significant difference in focus on the management of staff among the government and private hospitals is accepted (p = 0.847 at [alpha] of 0.05, mean difference = -0.053 and Levene's p = 0.632 and means range from 6.04-6.09) showing that both type of hospitals keep their staff trained and happy.

[H.sub.0]2f : There is no difference in the marketing information strategies among government and private hospitals.

The null hypothesis that there is no significant difference in the scores of marketing information strategies between government and private hospitals (p = 0.241 at [alpha] of 0.05, mean difference = 0.73 and Levene's p = 0.681 and means range from 2.88-3.77 for government and private hospitals respectively). The low mean score indicates that hospitals do not go in for information management. Although previous studies show that information management is highly correlated with marketing effectiveness and current profitability still the hospitals are not managing information systems.

[H.sub.0]2g : There is no difference in the marketing planning strategies between government and private hospitals.

Low scores on marketing planning (means are 3.48 for government hospitals and 4.20 for private hospitals) show lack of focus on this driver by all. Further the null hypothesis of no significant difference in the marketing planning scores between government and private hospitals is not rejected (p = 0.260 at [alpha] of 0.05, mean difference = -0.73 and Levene's p = 0.131)

[H.sub.0]2h : There is no difference in the marketing implementation strategies among government and private hospitals.

Non-rejection of hypothesis indicates that there is no significant difference in scores of the marketing implementation strategies between the government and private hospitals (p = 0.392 at [alpha] of 0.05, mean difference = -0.273 and Levene's p = 0.597). Average mediocre scores showed that the implementation process in the hospitals is just on an average level (the means are 4.95 for government and 5.22 for private hospitals).

[H.sub.0]3 : Strategic marketing variables are not related to target customer of the hospitals.

The managements of the hospitals were asked to identify their target patients. This test was performed so that it could be known what type of strategies attracted the patients to the hospitals. The results obtained from ANOVA (Table 2) show that only marketing communication is related with the target customer's income groups (p = 0.000 at [alpha] of 0.05) and thus the hypothesis of no significant difference between the scores of market drivers of hospital viz-a-viz target customer population is accepted with just one exception in case of marketing communication.

Perceived performance as related to Marketing Variable/Drivers

Perceived performance was measured in terms of marketing effectiveness (on market share growth relative to competition, growth in sales revenue, increasing sales to existing customers) and profitability (business unit profitability, return on investment, return on sales, reaching final goals), and then it was correlated with marketing drivers. From the matrix of correlations between marketing drivers and outcome in form of perceived effectiveness and profitability (Table 3), it has become obvious that the strategic marketing variables have a positive correlation with the effectiveness and profitability variables.

Further, it may be observed that drivers such as Pricing (r = 0.592, p = 0.020), Customer Management (r = 0.572 p = 0.026), Staff (r = 0.614, p = 0.015), Marketing Planning (r = 0.781, p = 0.001) and Market Information Management (r = 0.802, p = 0.000) are strongly related to Market Effectiveness. On the other hand Product Development (r = 0.535, p = 0.040), Customer Management (r = 0.802, p = 0.000), Market Information Management (r = 0.546, p = 0.035), and Marketing Planning (r = 0.648, p = 0.009) are strongly related to Current Profitability. All correlations are highly significant at [alpha] of 0.05.

Respondents also perceived that the focus on price promotions (r = 0.471 p = 0.076), expenditure on marketing communication (r = 0.133 p = 0.636), staffing policy (r = 0.439 p = 0.101), and factors leading to market effectiveness(r = 0.374, p = 0.169), are weekly related to current profitability. All these are perceived as expenses which eat into current profitability. Market effectiveness and current profitability are considered as separate constituents not supplementary but as substitute for each other (small correlation coefficient).

They also perceive that product development (r = 0.342, p = 0.213), marketing communication (r = 0.373, p = 0.171), marketing implementation (r = 0.289, p = 0.296), and current profitability (r = .374, p = 0.169) are not strongly related to market effectiveness. The irony is that profitability and market effectiveness are perceived as antitheses and not synergizing each other. Also, marketing communication is perceived as not important either for profitability or for market effectiveness. So they perceive that profitability and market effectiveness are weekly related or are just opposite to each other. So they chose either of them and not both of them as performance measure (agency effect).

Effect of Drivers on Marketing Outcomes

The relative influence of marketing drivers on marketing effectiveness was also measured. The strength and direction of relation is seen from the correlation matrix but regression equation helps one find the relative contribution of each marketing driver towards marketing effectiveness or current profitability. The general equation formed is a straight line and is given as

[Y.sub.i] = [[beta].sub.0] + [[beta].sub.i] [X.sub.i] + [e.sub.i]

Where:

[Y.sub.i] = Dependent or Criterion Variable (the market effectiveness or current profitability);

[X.sub.i] = Independent or Predictor Variable (marketing variables /drivers);

[[[beta].sub.0] = Intercept of the line;

[[[beta].sub.i] = Slope of the line; and

[e.sub.i] = Error associated with the ith observation.

Effect of Drivers on Marketing Effectiveness

Effect of Pricing on Marketing Effectiveness

It can be observed that the value of correlation coefficient 'r' is 0.592 and has high positive value. Here p = 0.020 (below 0.05) which leads to the conclusion that the linear model fits well, and marketing effectiveness does depend upon focusing on pricing strategies and is positively related.

Thus, Marketing Effectiveness = 3.038 + 0.396 (Pricing) + 0.149 I To check the empirical validity of the above equation, when one puts the value of Xi as 6.50 (empirically observed value for Pricing) one gets 5.76 as Yi which is very close to the empirical value for (Marketing effectiveness) 6.00. Thus, it is very close to the calculated value.

Effect of Customer Management strategies on Marketing Effectiveness

Marketing Effectiveness = 3.669 + 0.328 (Customer Management) + 0.13 II

(r=0.572, p = 0.026, which is below 0.05)

Effect of Staff on Marketing Effectiveness

Marketing Effectiveness = 0.227 + 0.847 (Staff) + 0.302 III

(r = 0.614, p = 0.15)

Effect of Market Information Management (MIM) on Marketing Effectiveness

Marketing Effectiveness = 4.079 + 0.391 (MIM) + 0.302 IV

(r = 0.802, p = 0.000)

Effect of Marketing Planning on Marketing Effectiveness

Marketing Effectiveness = 3.638 + 0.453 (Marketing Planning) + 0.101 V

(r = 0.781, p= 0.000)

From the above regression equations I to V, it can be inferred that the strategic marketing variables/drivers are strongly related to marketing effectiveness.

Effect of Drivers on Current Profitability

Similarly, the strategic marketing drivers/factors like Product Development, Customer Management, Market Information Management, and Marketing Planning show a strong effect on Current Profitability.

Effect of Product Development on Current Profitability

Current Profitability = 0.912 (Product Development) - 0.314 + 0.399 VI

(r = 0.535, p = 0.040)

Effect of Customer Management Strategies on Current Profitability

Current Profitability = 0.551 (Customer Management) + 2.032 + 0.114 VII

(r = 0.802, p = 0.000)

Effect of Marketing Information Management on Current Profitability

Current Profitability = 0.319 (MIM) + 3.832 + 0.136 VIII

(r = 0.546, p = 0.035)

Effect of Marketing Planning on Current Profitability

Current Profitability = 0.451 (Marketing Planning) + 3.165 + 0.147 IX

(r = 0.648, p = 0.009).

From equations VI to IX it is observed that Current Profitability is positively related and affected by the marketing variables/drivers. Thus the hospitals should strive to formulate the strategies and implement them in such a way that they gain maximum profits out of it and can have an effective market in the region.

Multiple Regression Model

Further, to find out joint effect of multiple drivers acting simultaneously, researchers tried a multiple regression model. In this, only a few marketing variables which had shown a higher correlation (> 0.6), were regressed with marketing effectiveness or current profitability. When the variables like Pricing, Customer Management, Staff, Marketing Information Management, and Marketing Planning were regressed with marketing effectiveness the regression equation obtained was:

Marketing Effectiveness = 0.223 (Pricing) - 0.269 (Customer Management) + 0.312 (Staff) - 0.012 (Marketing Information Management) + 0.544 (Marketing Planning) + 1.523 X

It may be noted that the coefficient of customer management and marketing information management negatively effect the scores of marketing effectiveness. The R for the regression equation is 0.882 and the [R.sup.2] is 0.779, showing that on the whole these five factors/ drivers have a strong effect on marketing effectiveness. The relationship is proved by the ANOVA where the p-value was 0.009 at [alpha] of 0.05. The marketing strategy elements/drivers, which show strong relationship with Current Profitability, were then regressed on current profitability.

Keeping the marketing strategy variables in mind Current Profitability can be calculated by the following equation:

Current Profitability = 0.324 (Product Development) + 0.772 (Customer Management) + 0.473 (Marketing Information Management) - 0.762 (Marketing Planning) + 0.650 XI

Where R = 0.824, [R.sup.2] = 0.678, and the p-value from the ANOVA test was found to be 0.015 at [alpha] 0.05. This proves the appropriateness of the equation as a whole.

It can also be inferred that marketing planning is considered as redundant activity, which strongly and negatively affect corporate profitability. Similarly, coefficient of marketing planning negatively affects the score of corporate profitability. This may be because of mental dissonance/conflicts in the minds of the respondents, which had arisen due to mismatch between customer expectation and owners' expectation (performance appraisal system).

Conclusion

From the research, one can conclude that as the efficiency of marketing strategies increases, the marketing effectiveness and current profitability will also increase in the same direction. The hospitals in the region (both government and private) are giving emphasis on marketing drivers like staff, customer management, product development and pricing but are not emphasizing on marketing planning and marketing information management. If the two types of hospitals give equal importance to all the drivers, they could achieve higher penetration in the market. Further, these strategies are strongly and positively related to the market-effectiveness and current profitability.

Multiple regression equation measuring the effect of the marketing strategies on the marketing effectiveness and current profitability found a change in the value of regression coefficients. There were even some negative coefficient values in the equations. It was found that customer satisfaction and marketing information management increased the marketing effectiveness when regressed alone, but during multiple regression the values for these coefficients became negative. The exact reason for the difference is not known but the perceived reason could be that there is some problem with the resource allocation ('either this or that dilemma'). Hospital management considers these two variables to be important during the planning stages of the strategies but during implementation they might be diverting resources from the customer management ([[beta].sub.i] = -0.269) and information management ([[beta].sub.i] = -0.012) to some other drivers that they consider more important in affecting marketing effectiveness. Similarly, the equation formed with current profitability and marketing strategy variables affecting it showed that while measuring profitability, hospitals in Chandigarh intend to neglect marketing planning ([[beta].sub.i] = -0.762).

Implication for policy makers and Managers

From the research a 2 x 2 matrix could be proposed for future analysis, which can help hospitals achieve higher marketing effectiveness and current profitability (Figure 1).

[FIGURE 1 OMITTED]

Marketing Effectiveness and Current Profitability are kept on the X and Y axes respectively and the plane is divided on the basis of high and low effectiveness and profitability; four quadrants are formed which decide four likely positions for a hospital. Any hospital management would try to reach the Desired Zone (QIII) from whichever quadrant they stand. The hospitals should be able to analyse themselves by conducting the internal analysis such as the balanced score card method from which they would come to know the exact marketing elements where they may be lagging behind. No hospital would like to fall in QI (Undesired Zone), where there is low Profitability and low Effectiveness. They would try and reach either QII or QIV but preferably should work on the required strategies to reach QIII for high Marketing Effectiveness and high Current Profitability.

Any hospital, which is in QII quadrant (high Marketing Effectiveness and Low Current Profitability), should work on the strategies like Product Development, Customer Management, Marketing Planning, Marketing Implementation, and Pricing to reach QIII. If a hospital is in QIV (high Current Profitability and low Marketing Effectiveness), it will have to work on strategies like Marketing Communication, Staff, Marketing Planning, and Marketing Information Management to reach QIII.

Managers and policy makers can use these regression models to find their marketing effectiveness and profitability. Further, they can incorporate these marketing output measures in the appraisal systems of the employees. Such a new system will be focused on customers, driven by marketing, and oriented towards profitability. Such a system will minimize managers decision deviated by agency effect. Also, it is found in the multiple regression equation that the mutual effect of different marketing variables/drivers does not appear to be synergetic, although, one by one, each driver is positively correlated with marketing output measures. Such paradox can be hypothesized to be caused by mental dissonance of marketing administrators, due to mismatch between how they are appraised and how they ought to be making decisions in competitive settings. Thus the proposed matrix can reduce this kind of conflicts and set up a framework of decision making even in a bureaucratic set-up. As observed, the lesser aggressiveness of government hospitals may decrease their market share particularly for middle and upper income patient segments. Policies have to be designed in such a manner that government hospitals also start catering at least to three economic segments delivering differentiated services and pricing accordingly. The message for them is that future survival is in competing with competitors and having always a competitive edge and not with a governmental edge.

Annexure I

(Adapted from Douglas W. Vorhies, Niel A. Morgan, 'Benchmarking Marketing Capabilities for Sustainable Competitive Advantage', Journal of Marketing, Vol. 69, January 2005)

Questionnaire

Name of the hospital: --

Address: --

Year of establishment: --

Approximate number of out-patients per day: --

Approximate number of in-patients in the hospital at this time: --

Number of beds in the hospital: --

Have you made the policies of your hospital keeping in knowledge the policies of your competitors?

Yes [] No []

If yes, please answer the following questions:

Who is your target customer (in terms of price):

Please rate your hospital (unit) in terms of its marketing capabilities in the following statements. (-3 refers to extreme dissatisfaction and 3 refers to extreme satisfaction.)

Pricing:

You use the pricing skills and -3 -2 -1 0 1 2 3
systems to respond quickly to market
changes

You have the knowledge of -3 -2 -1 0 1 2 3
competitors' pricing tactics

You are doing an effective job of -3 -2 -1 0 1 2 3
pricing product and services

Product development:

You are continuously monitoring -3 -2 -1 0 1 2 3
competitors prices and price changes

You have ability to develop new -3 -2 -1 0 1 2 3
services

You do test marketing of your new -3 -2 -1 0 1 2 3
services

You have been successfully launching -3 -2 -1 0 1 2 3
new services

You have been insuring that service -3 -2 -1 0 1 2 3
development efforts are responsive to
customer needs

Customer management and focus:

Patients ore given prompt and better -3 -2 -1 0 1 2 3
services

Patients ore treated with dignity -3 -2 -1 0 1 2 3
and respect

Medical condition of patients is -3 -2 -1 0 1 2 3
explained thoroughly to them

Feedback is obtained from patients -3 -2 -1 0 1 2 3

Specific needs of patients are taken -3 -2 -1 0 1 2 3
care of

Retaining the patients -3 -2 -1 0 1 2 3

Marketing communications:

You have being developing and -3 -2 -1 0 1 2 3
executing advertising programmes

Advertising management and creative -3 -2 -1 0 1 2 3
skills

Public relation skills -3 -2 -1 0 1 2 3

Brand image management skills and -3 -2 -1 0 1 2 3
processes

Managing corporate image and -3 -2 -1 0 1 2 3
reputation

Staffing:

Giving staff the training they need -3 -2 -1 0 1 2 3
to be effective

Effective staff control system -3 -2 -1 0 1 2 3

Professional and competent staff -3 -2 -1 0 1 2 3

Marketing information management:

Gathering information from the -3 -2 -1 0 1 2 3
customers and competitors

Using market research skills to -3 -2 -1 0 1 2 3
develop effective marketing
programmes

Tracking customers wants and needs -3 -2 -1 0 1 2 3

Making full use of your marketing -3 -2 -1 0 1 2 3
research information

Analysing your market information -3 -2 -1 0 1 2 3

Marketing planning:

Marketing planning skills -3 -2 -1 0 1 2 3

Ability to effectively segment and -3 -2 -1 0 1 2 3
target market

Marketing management skills and -3 -2 -1 0 1 2 3
processes

Developing creative marketing -3 -2 -1 0 1 2 3
strategies

Thoroughness of marketing planning -3 -2 -1 0 1 2 3
process

Marketing implementation:

Allocating marketing resources -3 -2 -1 0 1 2 3
effectively

Organizing to deliver marketing -3 -2 -1 0 1 2 3
programmes effectively

Translating marketing strategies -3 -2 -1 0 1 2 3
into actions

Executing marketing strategies -3 -2 -1 0 1 2 3
quickly

Monitoring marketing performance -3 -2 -1 0 1 2 3

Please evaluate the performance of your business over the last year.
(-3 if it is much worse and +3 if it is much better)

Market effectiveness:

Market share growth relative to -3 -2 -1 0 1 2 3
competitors

Growth in sales revenue -3 -2 -1 0 1 2 3

Acquiring new customers -3 -2 -1 0 1 2 3

Increasing sales to existing -3 -2 -1 0 1 2 3
customers

Market profitability:

Business unit profitability -3 -2 -1 0 1 2 3

Return on investment -3 -2 -1 0 1 2 3

Return on sale -3 -2 -1 0 1 2 3

Reaching financial goals -3 -2 -1 0 1 2 3

Thank you for your kind cooperation

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Anand Sharma * Sumesh Singh Dadwal * Sandeep Singh Mahal *

* Pharmaceutical Management, National Institute of Pharmaceutical Education and Research, Mohali, India.

Table 1 : Cross-table between customer segment and preferred
hospital type.

Type of hospital Target customer groups/Income Total

 Low income High income
 (< Rs 2 lakh/year) (> Rs 2 lakh/year)

Government 8 0 8
Private 0 7 7
Total 8 7 15

Lower income patients are targets of government hospitals and upper
segment patients are targets of private hospitals.

Table 2 : ANOVA For Scores of Marketing Variables between LIG and HIG

 ANOVA

 Sum of Mean
 Squares df Square

Pricing Between Groups 0.464 1 0.464
 Within Groups 14.894 13 1.146
 Total 15.358 14

Product Development Between Groups 0.194 1 0.194
 Within Groups 3.206 13 0.247
 Total 3.400 14

Customer Management Between Groups 0.422 1 0.422
 Within Groups 20.493 13 1.576
 Total 20.915 14

Marketing Between Groups 39.781 1 39.781
Communication Within Groups 5.249 13 0.404
 Total 45.029 14

Staff Between Groups 0.011 1 0.011
 Within Groups 3.589 13 0.276
 Total 3.600 14

Marketing Information Between Groups 3.000 1 3.000
Management Within Groups 25.869 13 1.990
 Total 28.869 14

Marketing Planning Between Groups 1.962 1 1.962
 Within Groups 18.395 13 1.415
 Total 20.357 14

Marketing Between Groups 0.290 1 0.290
Implementation Within Groups 4.814 13 0.370
 Total 5104 14

 ANOVA

 F Sig.

Pricing 0.405 0.535

Product Development 0.785 0.392

Customer Management 0.268 0.613

Marketing 98.532 0.000
Communication

Staff 0.039 0.847

Marketing Information 1.508 0.241
Management

Marketing Planning 1.387 0.260

Marketing 0.782 0.392
Implementation

Table 3: Matrix of correlation between marketing Drivers and marketing
outcomes

 Pricining Product
 Develop-
 ment

Pricing Pearson Correlation 1 0.663 ***
 Sig. Sig. (2-tailed) 0.007
 N 15 15

Proche Pearson Correlation 0.663 ** 1
Development Sig. Sig. (2-tailed) 0.007
 N 15 15

Customer Mgt Pearson Correlation 0.547* 0.663 **
 Sig. Sig. (2-tailed) 0.035 0.007
 N 15 15

Marketing Pearson Correlation 0.217 0.402
Communication Sig. Sig. (2-tailed) 0.438 0.137
Mgt N 15 15

Staff Pearson Correlation 0.408 0.014
 Sig. Sig. (2-tailed) 0.131 0.960
 N 15 15

Market Pearson Correlation 0.369 0.275
Information Mgt Sig. Sig. (2-tailed) 0.176 0.322
 N 15 15

Marketing Pearson Correlation 0.462 0.524 *
Planning Sig. Sig. (2-tailed) 0.083 0.045
 N 15 15

Marketing Pearson Correlation 0.360 0.747 **
Implementation Sig. Sig. (2-tailed) 0.187 0.001
 N 15 15

Market Pearson Correlation 0.592 * 0.342
Effectiveness Sig. Sig. (2-tailed) 0.020 0.213
 N 15 15

Current Pearson Correlation 0.471 0.535 *
Profitability Sig. Sig. (2-tailed) 0.076 0.040
 N 15 15

 Cus- Mar
 tomer keting
 Manage- Commu-
 ment nication
 Mgt

Pricing Pearson Correlation 0.547 * 0.217
 Sig. Sig. (2-tailed) 0.035 0.438
 N 15 15

Proche Pearson Correlation 0.663 ** 0.402
Development Sig. Sig. (2-tailed) 0.007 0.137
 N 15 15

Customer Mgt Pearson Correlation 1 0.279
 Sig. Sig. (2-tailed) 0.313
 N 15 15

Marketing Pearson Correlation 279 1
Communication Sig. Sig. (2-tailed) 313
Mgt N 15 15

Staff Pearson Correlation 0.389 -0.040
 Sig. Sig. (2-tailed) 0.152 0.888
 N 15 15

Market Pearson Correlation 0.675 ** 0.423
Information Mgt Sig. Sig. (2-tailed) 0.006 0.117
 N 15 15

Marketing Pearson Correlation 0.842 ** 0.469
Planning Sig. Sig. (2-tailed) 0.000 0.078
 N 15 15

Marketing Pearson Correlation 0.692 ** 0.316
Implementation Sig. Sig. (2-tailed) 0.004 0.251
 N 15 15

Market Pearson Correlation 0.572 * 0.373
Effectiveness Sig. Sig. (2-tailed) 0.026 0.171
 N 15 15

Current Pearson Correlation 0.802 ** 0.133
Profitability Sig. Sig. (2-tailed) 0.000 0.636
 N 15 15

 Staff Market
 Informa-
 tion Mgt

Pricing Pearson Correlation 0.408 0.369
 Sig. Sig. (2-tailed) 0.131 0.176
 N 15 15

Proche Pearson Correlation 0.014 0.275
Development Sig. Sig. (2-tailed) 0.960 0.322
 N 15 15

Customer Mgt Pearson Correlation 0.389 0.675 **
 Sig. Sig. (2-tailed) 0.152 0.006
 N 15 15

Marketing Pearson Correlation -0.040 0.423
Communication Sig. Sig. (2-tailed) 0.888 0.117
Mgt N 15 15

Staff Pearson Correlation 1 0.638 *
 Sig. Sig. (2-tailed) 0.010
 N 15 15

Market Pearson Correlation 0.638 * 1
Information Mgt Sig. Sig. (2-tailed) 0.010
 N 15 15

Marketing Pearson Correlation 0.481 0.936 **
Planning Sig. Sig. (2-tailed) 0.069 0.000
 N 15 15

Marketing Pearson Correlation 0.044 0.304
Implementation Sig. Sig. (2-tailed) 0.878 0.271
 N 15 15

Market Pearson Correlation 0.614 * 0.802 **
Effectiveness Sig. Sig. (2-tailed) 0.015 0.000
 N 15 15

Current Pearson Correlation 0.439 0.546 *
Profitability Sig. Sig. (2-tailed) 0.101 0.035
 N 15 15

 Market- Mar
 ing Plan- keting
 ning Imple-
 menta-
 tion

Pricing Pearson Correlation 0.462 0.360
 Sig. Sig. (2-tailed) 0.083 0.187
 N 15 15

Proche Pearson Correlation 0.524 * 0.747 **
Development Sig. Sig. (2-tailed) 0.045 0.001
 N 15 15

Customer Mgt Pearson Correlation 0.842 ** 0.692 **
 Sig. Sig. (2-tailed) 0.000 0.004
 N 15 15

Marketing Pearson Correlation 0.469 0.316
Communication Sig. Sig. (2-tailed) 0.078 0.251
Mgt N 15 15

Staff Pearson Correlation 0.481 0.044
 Sig. Sig. (2-tailed) 0.069 0.878
 N 15 15

Market Pearson Correlation 0.936 ** 0.304
Information Mgt Sig. Sig. (2-tailed) 0.000 0.271
 N 15 15

Marketing Pearson Correlation 1 0.473
Planning Sig. Sig. (2-tailed) 0.075
 N 15 15

Marketing Pearson Correlation 0.473 1
Implementation Sig. Sig. (2-tailed) 0.075
 N 15 15

Market Pearson Correlation 0.781 0.289
Effectiveness Sig. Sig. (2-tailed) 0.001 0.296
 N 15 15

Current Pearson Correlation 0.648 ** 0.407
Profitability Sig. Sig. (2-tailed) 0.009 0.132
 N 15 15

 Market Current
 Effec- Profit-
 tiveness ability

Pricing Pearson Correlation 0.592 0.471
 Sig. Sig. (2-tailed) 0.020 0.076
 N 15 15

Proche Pearson Correlation 0.342 0.535 *
Development Sig. Sig. (2-tailed) 0.213 0.040
 N 15 15

Customer Mgt Pearson Correlation 0.572 * 0.802 **
 Sig. Sig. (2-tailed) 0.026 0.000
 N 15 15

Marketing Pearson Correlation 0.373 0.133
Communication Sig. Sig. (2-tailed) 0.171 0.636
Mgt N 15 15

Staff Pearson Correlation 0.614 * 0.439
 Sig. Sig. (2-tailed) 0.015 0.101
 N 15 15

Market Pearson Correlation 0.802 * 0.546 *
Information Mgt Sig. Sig. (2-tailed) 0.000 0.035
 N 15 15

Marketing Pearson Correlation 0781 ** 0.648 **
Planning Sig. Sig. (2-tailed) 0.001 0.009
 N 15 15

Marketing Pearson Correlation 0.289 0.407
Implementation Sig. Sig. (2-tailed) 0.296 0.132
 N 15 15

Market Pearson Correlation 1 0.374
Effectiveness Sig. Sig. (2-tailed) 0.169
 N 15 15

Current Pearson Correlation 0.374 1
Profitability Sig. Sig. (2-tailed) 0.169
 N 15 15

** Correlation is significant at the 0.01 level (2-tailed).

* Correlation is significant at the 0.05 level (2-tailed).

Coefficients (a)

 Unstandardized Standardized
 Coefficients Coefficients

Correlations

Model B Std. Error Beta

1 (Constant) 1.523 2.069
 Pricing 0.223 0.137 0.333
 Customer Mgt -0.269 0.243 -0.469
 Staff 0.312 0.399 0.226
 Marketing Info 1.237E-02 0.423 -0.025
 Mgt
 Marketing 0.544 0.595 0.936
 Planning

 Correlations

Model t Sig. Zero-order Partial Part

1 (Constant) 0.736 0.480
 Pricing 1.627 0.138 0.592 0.477 0.255
 Customer Mgt -1.107 0.297 0.572 -0.346 -0.174
 Staff 0.782 0.454 0.614 0.252 0.123
 Marketing Info -0.029 0.977 0.802 -0.010 -0.005
 Mgt
 Marketing 0.913 0.385 0.781 0.291 0.143
 Planning

(a) Dependent Variable: Marketing Effectivenessa

Coefficients (a)

 Unstandardized Standardized
 Coefficients Coefficients

Correlations

Model B Std. Error Beta

1 (Constant) 0.650 2.313
 Product 0.324 0.522 0.190
 Development
 Customer Mgt 0.722 0.285 1.051
 Marketing Info 0.473 0.474 0.810
 Mgt
 Marketing -0.762 0.735 -1.095
 Planning

 Correlations

Model t Sig. Zero-order Partial Part

1 (Constant) 0.281 0.785
 Product 0.620 0.549 0.535 0.192 0.111
 Development
 Customer Mgt 2.530 0.030 0.802 0.625 0.454
 Marketing Info 0.998 0.342 0.546 0.301 0.179
 Mgt
 Marketing -1.037 0.324 0.648 -0.311 -0.186
 Planning

(a) Dependent Variable: Marketing Effectivenessa