Keywords

Decision-making Styles, Corporate Executives, Vigilance, Hypervigilance, Defensive Avoidance

Introduction

Every day, people are inundated with decisions, big and small. Decision making is a fundamental function in management and the success or failure of executives and the organisation mainly hinges upon the quality of decisions. Simon (1954) revealed that “decision making role” is the “heart of executive activities”. Decision-making is the process of identifying and choosing alternatives based on the values, preferences and beliefs of the decision-maker. These decisions often have personal, social, political, economic and environmental consequences. Decision-making is approached by managers in different ways-some managers make an extensive analysis via more information with an objective approach and some take decisions by intuition. Some of them make a decision independently and some wait for others’ guidance. Some of them behave hasty in decision making process and some are too careful to the extent that they avoid making a decision.

Some executive copes with the stress and makes decision making depending on their age/maturity, experience, level of decision making and other factors. Economists and policymakers have observed that demographic factors both intrinsic as well as extrinsic like age, gender, marital status, qualifications, occupation, annual income, geographic location etc have an impact on the level of risk that investors take further based on their behavioral and decisionmaking aspect (Jain & Mandot, 2012).

The objectives of the study are to establish the existence or otherwise of the influence of the demographic factors in decision-making styles of corporate executives In this study, the influence of demographic factors on decision-making styles of Indian corporate executives has been studied empirically. Demographic factors such as age, gender, education, work experience, managerial level and income have been considered. The executives have been assessed for their decision-making styles by conflict theory model of decision making devised by Janis & Mann (1977). According to this model, executives adopt one of the three styles of decision-making when faced with conflicting situations. They are vigilance style, hyper vigilance style and defensive avoidance (procrastination, rationalisation and buck passing) style.

Understanding the influence of various factors in decision-making adds to the knowledge bank of existing research on decision-making and induces more research on the field. This also helps in recruitment of suitable executives to fit the company/s objectives, job assignment and training.

Literature Study

The process of decision-making is one of the most complex mechanisms of human thinking, as various factors and courses of action intervene in it, with different results. (Orasanu and Connolly (1993) define it as a series of cognitive operations performed consciously, which include the elements from the environment in a specific time and place. Narayan and Corcoran- Perry (1997) consider decision making as the interaction between a problem that needs to be solved and a person who wishes to solve it within a specific environment.

A manager needs to make sound/rational decisions as a part of his regular activities and he makes hundreds of decisions on a regular basis in various situations. Decision-making is an essential component of the management and decision implies the end of deliberation and the beginning of action. Risk is an inevitable part of every decision. For most of the choices people make every day, the risks are small. But on a corporate scale, the implications (both upside and downside) can be enormous.

In decision-making, various alternatives are to be considered critically and the best one is to be selected. Here, the available business environment also needs careful consideration. The alternative selected may be correct or may not be correct and this will be decided in the future, as per the results available from the decision already taken. The manager needs in-built/ acquired capacity to select the best alternative. The benefits of correct decision-making will be available only when the best alternative is selected for implementation.

Decision-making styles can vary among the corporate executives based on many factors such as personality, organisation context, roles & responsibilities of the executives, goals of the organisations and decision structure. Influence of self-esteem on decision-making styles has been observed among Indian corporate executives (Rebellow & Patra, 2016). Managers in enterprises adopt different decision-making styles to cope with different situations based on the time and information available, the ethics involved the consequences of decisions taken, the goals of the organization, organization structure and the responsibility accountability. A study conducted on Indian corporate executives indicated the significant difference in decisionmaking styles between public and private sector proving organisational factor (Patra & Rebellow, 2017). How the individual copes with the stress in a given situation depends on one’s age/ maturity, experience, level of decision making and other factors.

Janis & Mann (1977) propose in the conflict theory of decision making that individuals cope with conflicting situations via three decision styles. The vigilance style requires thorough information search, unbiased assimilation of new information and other characteristics of high quality decision making. All the other styles viz, hyper vigilance (panic) and defensive avoidance (procrastination, buck passing and rationalization) are occasionally adaptive in saving time, effort and emotional wear and tear, especially for routine decisions that do not have series consequences. But they often result in defective decision making when the decision maker is confronted with a vital choice that has series consequence for oneself or for the organization on whose behalf one is making the decision.

The demographic factors covered in this study are age, gender, education, experience, managerial level and income. The term managerial level is a line of demarcation between various managerial positions in an organization. The level of management determines a chain of command, the decision content, the amount of authority and status enjoyed by any managerial position. The levels of management has been classified in three broad categories for this study namely, i) Top level/Administrative level, ii) Middle level/Executory and iii) Junior/Low level/First-line managers.

The decision-making style of managers vary due to the relevance they allocate to the task, the decision maker, and the environmental factors that determine the decision process and Gender is an important factor (Lizárraga et al., 2007). Women place more value on time and money; they are more concerned about the consequences that may derive from the decision. They are more aware of the constraints and their emotions are more important to them in the decision process. Men assign more importance to the analysis of the information required to carry out the decision and to the definition of the objectives of the decision.

The decision-making process depends on the differences amongst managers’ values, attitudes, education, organisation, managerial level. This difference amongst managers is because of the difference in experience, analytical ability, in forming perception and processing of information, scope of consultation, and degree of freedom of choice, availability of resources and trust and rapport between the managers. Executives have to take decisions immaterial of how the companies are performing (poorly or well). Results of a research on organisational performance indicated that problems/opportunities and organisational performance affected the decision-making process by relatively inexperienced executives (Fredrickson, 1985).

Behavioral aspects have been found to have significant role in investment decision making. Demographic factors such as gender, age, marital status, education, income, and family members have influence on investors’ risk tolerance and investment preferences (Lufti, 2010). Demographic factors are considered as one of the decisions influencing factor among others (Khanam, 2017). In an empirical study, gender was found to have significant influence on the investment pattern and decision making of respondents. (Chavali & Mohanraj, 2016). A study was conducted for the purpose of examining the effect of demographic factors like income level, age, gender, educational background, and quality level on predispositions of individual investors operating in Borsa Istanbul (BIST) towards risk taking (Gumus & Dayioglu, 2015). In the analyses, it was found that the factors have significant effect on the risk perception of individual investors during their portfolio investments.

To date, only a few number of research studies have investigated the influence of demographic factors and decision making styles of corporate executives that too mostly in countries other than India. An effort has been made in this study to assess the variation in decision making styles of public and corporate executives of India with respect to the demographic factors. This study has possible implications in management practices to be adapted, inter change/adaptability of management techniques, selection of right kind of executives for the jobs and assignment of suitable jobs for the right manager, provision of training and support for decision makers in corporate sectors.

Some of the research findings on the influence of demographic factors on decision making styles is summarised as below:

100 investors from twin cities of Pakistan (Rawalpindi and Islamabad) were selected and study was conducted to explore the effect of demographic factors on investor’s level of risk tolerance regarding the choice of investment. Results indicate that demographic factors of investors such as academic education, income level, investment knowledge, and investment experience affect the investor’s level of risk tolerance, while investor’s gender, marital status, occupation, and family size showed no effect on investor’s level of risk tolerance (Sadiq & Ishaq, 2014).

673 university students from Australia, Malaysia and Singapore were tested (Brown et al., 2011) using conflict model of decision making. Women reported higher scores on hyper vigilance than males in all three countries. Significant positive correlation was found between age and vigilant decision making and negative correlation with non-vigilant decision making. Among Australian respondents, women scored significantly higher in buck passing than males. No significant differences could be found on gender. Relationship between level of risk and demographic factors of investors confined to Rajasthan state were explored (Jain & Mandot, 2012). The results indicated a negative correlation between Marital Status, Gender, Age, Educational Qualification and Occupation of the investors. Positive correlation was found between Cities, Income Level and Knowledge of the investors. The influence of gender and age in the decision process was investigated among 589 participants (294 men and 295 women) of ages between 18-80 years old (Lizárraga et al., 2007). The results revealed significant differences in participants’ perception of the factors that determine their decision processes with respect to gender and age.

Study on 222 American and Spanish business executives was conducted to explore sex differences in ethical judgments. No significant differences between males and females were found on ethical judgments. Females exhibited higher intentions to act more ethically than males (Valentine & Rittenburg, 2007). Further research was warranted to develop a clearer understanding of the linkage between ethical judgment and intention to act in an ethical manner.

A meta-analysis was conducted to compare risk-taking tendencies of male and female participants (Byrnes et al., 1999) were compared. Results indicated greater risk taking in male participants and significant shifts in the size of the gender gap between successive age levels, the need for additional studies to clarify age trends also were indicated.

Research Framework

To find the existence or otherwise of influence of demographic factors on decision making styles of Indian corporate executives is the objective of this study. Keeping the objectives in mind, the research framework is formulated as below Figure 1.

Research Hypothesis

Null Hypotheses were formulated as below:

H₀: Age factor has no significant influence on decision-making styles of Indian Corporate Executives.

H_a: Age factor has significant influence on decision-making styles of Indian Corporate Executives.

H₀: Gender factor has no significant influence on decision-making styles of Indian Corporate Executives.

H_a: Gender factor has significant influence on decision-making styles of Indian Corporate Executives.

H₀: Experience factor has no significant influence on decision-making styles of Indian Corporate Executives.

H_a: Experience factor has significant influence on decision-making styles of Indian Corporate Executives.

H₀: Education factor has no significant influence on decision-making styles of Indian Corporate Executives.

H_a: Education factor has significant influence on decision-making styles of Indian Corporate Executives.

H₀: Managerial level has no significant influence on decision-making styles of Indian Corporate Executives.

H_a: Managerial level has significant influence on decision-making styles of Indian Corporate Executives.

H₀: Income factor has no significant influence on decision-making styles of Indian Corporate Executives.

H_a: Income factor has significant influence on decision-making styles of Indian Corporate Executives.

Methodology of the Study

Research Study

This is an organisational behavior study that analyses the influence of demographic factors (Independent variables) on Decision Making styles of Corporate Executives (dependent variables).

The following studies were carried out to assess the difference in decision making styles of Indian corporate executives with respect to demographic factors, namely age, gender, education, experience, managerial level and income.

Data Collection

Corporate Executives of India covering various demographic factors were selected under judgment sampling. After detailed literature study, one questionnaire on Decision Making Styles consisting of 56 questions including the questions from Flinders DMQ II (Mann, 1982) was prepared for response in Likert 5 scale. The decision-making styles questionnaire covered all the three styles of Decision making namely vigilance, hyper vigilance and decision avoidance. 17 Questions on vigilance, 14 on hyper vigilance and 25 on defensive avoidance (7 on buck passing, 10 on rationalization and 8 on procrastination) were prepared. Executives belonging to 15 public sector companies and 21 private sector companies were covered and 282 successful responses covering different demographic factors were received. The frequency distribution of the sample has been given in Table 1.

Table 1: Frequency Table
	Frequency	Percent	Valid Percent	Cumulative Percent
Age (Years)
Below 25	36	12.8	12.8	12.8
Between 25-35	90	31.9	31.9	44.7
Between 36-45	3	1.1	1.1	45.7
Between 46-55	57	20.2	20.2	66.0
Above 55	96	34.0	34.0	100.0
Total	282	100.0	100.0
Gender
Male	225	79.8	79.8	79.8
Female	57	20.2	20.2	100.0
Total	282	100.0	100.0
Education
Below Graduate	18	6.4	6.4	6.4
Graduate	163	57.8	57.8	64.2
Postgraduate	101	35.8	35.8	100.0
Total	282	100.0	100.0
Experience (Years)
Below 5	73	25.9	25.9	25.9
25.9	53	18.8	18.8	44.7
18.8	9	3.2	3.2	47.9
3.2	4	1.4	1.4	49.3
1.4	17	6.0	6.0	55.3
6.0	29	10.3	10.3	65.6
10.3	77	27.3	27.3	92.9
27.3	20	7.1	7.1	100.0
7.1	282	100.0	100.0
Sector
Public	154	54.6	54.6	54.6
Private	128	45.4	45.4	100.0
Total	282	100.0	100.0
Managerial Level
Junior	116	41.1	41.1	41.1
Middle	87	30.9	30.9	72.0
Top	79	28.0	28.0	100
Total	282	100.0	100.0
Income (INR/pm)
Below 40000	51	18.1	18.1	18.1
40000-69999	38	13.5	13.5	31.6
70000-89999	27	9.6	9.6	41.2
90000-150000	37	13.1	13.1	54.3
Above 150000	129	45.7	45.7	100
Total	282	100.0	100.0

The reliability test indicated Cronbach’s Alpha coefficient of 0.776, 0.840 and 0.927 for hypervigilance, vigilance and defensive avoidance styles of Decision-making. Kaise-Meyer Olkin (KMO) measure of 0.796, 0.847 and 0.793 for hypervigilance, vigilance and defensive avoidance styles of Decision-making indicate a good sampling adequacy. The reliability and summary statistics of the data is given as Table 2. Data Analysis was made using SPSS 23 and other statistical tools.

Table 2: Reliability And Summary Item Statistics
	Hyper vigilance	Vigilance	Defensive avoidance
Cronbach Alpha	0.776	0.840	0.927
Cronbach Alpha based on standardized items	0.796	0.847	0.930
No of items	14	17	25
KMO of sampling Adequacy	0.809	0.682	0.793
Bartlett’s test of sphericity	1447.674	2117.111	4943.427
df	91	136	300
Sig.	0	0	0
Minimum	2.050	3.615	1.770
Maximum	3.143	4.457	3.291
Mean	2.578	4.161	2.220
Range	0.993	.823	1.521
Variance	.063	.041	.151

Results and Discussion

Hypothesis testing results (2 tail test with 5% level of significance) are given in fs 3a, b & c to 8a,b,& c.

Table 3a: Age-Vigilance Cross Tabulation
			Vigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Age	Below 25	Count	0	14	116	361	121	612
	25-35	Count	3	15	232	764	516	1530
	36-45	Count	0	0	3	12	36	51
	46-55	Count	4	5	134	591	235	969
	Above 55	Count	1	24	159	799	649	1632
Total		Count	8	58	644	2527	1557	4794

Table 3b : Age-Hypervigilance Crosstabulation
			Hyper vigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Age	Below 25	Count	38	139	219	84	24	504
	25-35	Count	147	472	423	173	45	1260
	36-45	Count	2	14	23	3	0	42
	46-55	Count	105	317	251	97	28	798
	Above 55	Count	238	506	370	168	62	1344
Total		Count	530	1448	1286	525	159	3948

Percentages and totals are based on responses. Chi sq.=6.93821E-14

Table 3c : Age-Defensive Avoidance Crosstabulation
			Defensive Avoidance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Age	Below 25	Count	135	322	253	136	54	900
	25-35	Count	581	856	555	184	74	2250
	36-45	Count	15	23	25	10	2	75
	46-55	Count	392	565	348	94	26	1425
	Above 55	Count	826	841	509	178	46	2400
Total		Count	1949	2607	1690	602	202	7050

1. H₀: Age factor has no significant influence on decision-making styles of Indian Corporate Executives.

H_a: Age factor has significant influence on decision-making styles of Indian Corporate Executives.

Chi square tests indicate significance level less than 0.05 and hence hypothesis is rejected. Age has significant influence on all three decision-making styles of executives.

2. H₀: Gender factor has no significant influence on decision-making styles of Indian Corporate Executives.

Table 4a: Gender-Vigilance Crosstabulation
			Vigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Gender	Male	Count	5	45	469	1969	1337	3825
	Female	Count	3	13	175	558	220	969
Total		Count	8	58	644	2527	1557	4794

Table 4b:Gender-Hypervigilance Crosstabulation.
			Hypervigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Gender	Male	Count	441	1196	973	409	131	3150
	Female	Count	89	252	313	116	28	798
Total		Count	530	1448	1286	525	159	3948

Table 4c: Gender-Defensiveavoidance Crosstabulation
			Defensive Avoidance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Gender	Male	Count	1638	2113	1294	436	143	5624
	Female	Count	311	494	396	166	59	1426
Total		Count	1949	2607	1690	602	202	7050

H_a: Gender factor has significant influence on decision-making styles of Indian Corporate

Chi square test indicates significance level less than 0.05 in all three decision-making styles suggesting the rejection of null hypothesis. Hence gender has significant influence on decision-making styles.

3. H₀: Education factor has no significant influence on decision-making styles of Indian Corporate Executives.

Table 5a: Education-Vigilance Crosstabulation
			Vigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Education	Graduate	Count	3	35	352	1483	898	2771
	Post Graduate	Count	3	18	250	885	561	1717
	Below Graduation	Count	2	5	42	159	98	306
Total		Count	8	58	644	2527	1557	4794

Table 5b: Education-Hypervigilance Crosstabulation
			Hypervigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Education	Graduate	Count	317	832	759	302	72	2282
	Post Graduate	Count	182	545	429	174	84	1414
	Below Graduation	Count	31	71	98	49	3	252
Total		Count	530	1448	1286	525	159	3948

Table 5c:Education-Defensiveavoidance Crosstabulation.
			Defensive Avoidance					Total
			Very Frequently	Frequently	Sometimes	Rarely	Never
Education	Graduate	Count	2218	3163	1975	662	207	8225
	Post Graduation	Count	1513	2037	1106	505	164	5325
	Other	Count	117	202	150	62	19	550
Total		Count	3848	5402	3231	1229	390	14100

H_a: Education factor has significant influence on decision-making styles of Indian Corporate Executives.

Chi square test indicates significance of more than 0.05 in case of vigilance and less than 0.05 in hyper vigilance and defensive avoidance.

Education may not have significant influence on vigilant decision-making styles of executives but has significant influence on other two styles namely, hypervigilance and defensive avoidance styles.

4. H₀: Experience factor has no significant influence on decision-making styles of Indian Corporate Executives.

H_a: Experience factor has significant influence on decision-making styles of Indian Corporate Executives.

Table 6a: Experience-Vigilance Crosstabulation.
			Vigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Experience (years)	Upto 5	Count	1	22	242	606	370	1241
	6-10	Count	2	8	110	505	276	901
	11-15	Count	0	0	17	94	42	153
	16-20	Count	1	0	11	48	8	68
	21-25	Count	1	2	38	171	77	289
	26-30	Count	0	1	64	281	147	493
	31-35	Count	3	18	116	639	533	1309
	>35	Count	0	7	46	183	104	340
Total		Count	8	58	644	2527	1557	4794

Table 6b: Experience-Hypervigilance Crosstabulation
			Hypervigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Experience (years)	Upto 5	Count	76	327	410	164	45	1022
	6-10	Count	86	298	241	96	21	742
	11-15	Count	40	42	29	10	5	126
	16-20	Count	3	26	22	5	0	56
	21-25	Count	30	103	72	25	8	238
	26-30	Count	48	160	121	52	25	406
	31-35	Count	215	397	294	133	39	1078
	>35	Count	32	95	97	40	16	280
Total		Count	530	1448	1286	525	159	3948

Table 6c: Experience-Defensiveavoidance Crosstabulation
			Defensive Avoidance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Experience (years)	Upto 5	Count	372	646	468	244	95	1825
	6-10	Count	305	531	359	91	39	1325
	11-15	Count	117	72	36	0	0	225
	16-20	Count	35	46	19	0	0	100
	21-25	Count	132	161	110	14	8	425
	26-30	Count	175	298	171	70	11	725
	31-35	Count	648	686	416	139	36	1925
	>35	Count	165	167	111	44	13	500
Total		Count	1949	2607	1690	602	202	7050

Chi square test indicates significance level less than 0.05 in all three decision-making styles suggesting the rejection of null hypothesis. Hence Experience has significant influence on decision-making styles.

5. H₀: Managerial level factor has no significant influence on decision-making styles of Indian Corporate Executives.

H_a: Managerial level factor has significant influence on decision-making styles of Indian Corporate Executives.

Table 7a : Position-Vigilance Crosstabulation
			Vigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Managerial level	Junior	Count	4	27	313	1048	580	1972
	Middle	Count	1	11	169	774	524	1479
	Senior	Count	3	20	162	705	453	1343
Total		Count	8	58	644	2527	1557	4794

Table 7b: Position-Hypervigilance Crosstabulation
			Hyper vigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Managerial level	Junior	Count	177	560	588	231	68	1624
	Middle	Count	176	448	386	175	33	1218
	Senior	Count	177	440	312	119	58	1106
Total		Count	530	1448	1286	525	159	3948

Table 7c : Position-Defensiveavoidance Crosstabulation
			Defensive Avoidance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Managerial level	Junior	Count	680	1098	739	280	103	2900
	Middle	Count	583	832	509	183	68	2175
	Senior	Count	686	677	442	139	31	1975
Total		Count	1949	2607	1690	602	202	7050

Chi square test indicates significance level less than 0.05 in all three decision-making styles suggesting the rejection of null hypothesis. Hence Managerial level has significant influence on decision-making styles.

6. H₀: Income factor has no significant influence on decision-making styles of Indian Corporate Executives.

H_a: Incomefactor has significant influence on decision-making styles of Indian Corporate Executives.

Table 8a: Income-Vigilance Crosstabulation
			Vigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Income (INR/pm)	<40000	Count	3	16	159	473	216	867
	40000-69999	Count	0	8	57	320	261	646
	70000-89999	Count	2	0	35	279	143	459
	90000-150000	Count	0	3	74	374	178	629
	>150000	Count	3	31	319	1081	759	2193
Total		Count	8	58	644	2527	1557	4794

Table 8b: Income-Hypervigilance Crosstabulation
			Hyper vigilance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Income (INR/pm)	<40000	Count	46	227	305	111	25	714
	40000-69999	Count	56	220	160	70	26	532
	70000-89999	Count	79	129	123	40	7	378
	90000-150000	Count	58	192	174	71	23	518
	>150000	Count	291	680	524	233	78	1806
Total		Count	530	1448	1286	525	159	3948

Table 8c:Income-Defensive Avoidance Crosstabulation
			Defensive Avoidance					Total
			Never	Rarely	Sometimes	Frequently	Very frequently
Income (INR/pm)	<40000	Count	212	475	377	159	52	1275
	40000-69999	Count	259	385	193	81	32	950
	70000-89999	Count	220	287	135	19	14	675
	90000-150000	Count	239	369	219	73	25	925
	>150000	Count	1019	1091	766	270	79	3225
Total		Count	1949	2607	1690	602	202	7050

Chi square test indicates significance level less than 0.05 in all three decision-making styles suggesting the rejection of null hypothesis. Hence Income facto has significant influence on decision-making styles.

Conclusion

The Null Hypothesis results of the study have been summarised in the Table 9.

Table 9: Summary Of Results
Demographic factor	Vigilance	Hypervigilance	Defensive avoidance
AGE	Rejected	Rejected	Rejected
GENDER	Rejected	Rejected	Rejected
EDUCATION	Not Rejected	Rejected	Rejected
EXPERIENCE	Rejected	Rejected	Rejected
POSITION	Rejected	Rejected	Rejected
INCOME	Rejected	Rejected	Rejected

Earlier researchers have found that decision-making styles of investors/ managers are influenced by demographic factors. The present study indicates the significant influence of demographic factors on decision making styles. Only Education has been found to have no/ less significance that too only on Vigilance style of decision-making. Therefore it can be concluded that the results of present study is mostly in line with the previous research and the hypothetical framework has been proved.

The results of this study will add to the existing research bank on decision-making and will stimulate additional critical thought and research on decision-making theories in corporate sectors to refine further. This aspect needs to be considered while making recruiting and assigning key jobs to executives of corporate sectors.

Recommendations

Some of the results obtained in this study differ from those reported in a few of previous research works conducted elsewhere. This difference may be partially due to influence of other factors such as Personal factors and Environmental factors. A comprehensive and elaborate study covering all demographic factors, sample including multination’s corporate executives and a bigger sample is suggested to establish the influence or otherwise of demographic factors on the decision-making styles of corporate executives. The overlapping influence of personal, environmental and other factors if studied will give a comprehensive understanding.

Limitations

It is pertinent to add the limitations of this study. First of all, the number of respondents is relatively small. Secondly, the demographic aspects examined in this study are limited to gender, age, marital status, education, income and managerial level. Decision-making styles may also be affected by other demographic aspects, such as ethnic group, religion, marital status, geographical location and occupation. Thirdly, this study focuses on investors’ demographic factors and does not consider the personality factors, environmental factors and other psychological aspects.

Acknowledgement

The authors would like to thank Uttaranchal University for encouraging this research work. No funding/sponsorship have been availed for the research work.

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