Journal of Management Information and Decision Sciences (Print ISSN: 1524-7252; Online ISSN: 1532-5806)

Research Article: 2019 Vol: 22 Issue: 3

ROLE OF DEMOGRAPHIC FACTORS ON DECISION-MAKING STYLES OF INDIAN CORPORATE EXECUTIVES-PUBLIC AND PRIVATE SECTORS

A. Mohan Rebellow, Uttaranchal University

Pradeep Suri, Uttaranchal University

Citation Information: Rebellow, A. M., & Suri, P. (2019). Role of demographic factors on decision-making styles of Indian corporate executives-public and private sectors. Journal of Management Information and Decision Sciences, 22(3), 308-321.

Abstract

An empirical study to assess the role of demographic factors on decision styles of corporate executives. 282 Indian corporate executives covering 15 Public sector & 21 Private sector organizations with various demographic factors were selected under judgment sampling. Conflict decision style by Janis & Mann was employed to assess the decision-making styles of executives. A framework was formulated for hypothetical testing. The questionnaire covering all the three styles of Decision-making namely vigilance, hypervigilance and defensive avoidance was administered and the response was analysed using statistical tools. The results indicate that the demographic factors have a significant influence on all three decision-making styles namely, Vigilance, Hypervigilance and Defensive Avoidance styles of executives. Understanding the influence of demographic factors on decision-making styles will add to the existing research bank on Decision-making and will stimulate additional critical thought and stimulate further research. This understanding plays a vital role on successful geographical expansion of enterprises and proper selection and placement of executives at key jobs for the success of the enterprises. These findings also have implications for global firms, particularly regarding codes of conduct and ethics training.

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.

Figure 1:Influence Of Demographic Factors On Decision-Making Styles.

Research Hypothesis

Null Hypotheses were formulated as below:

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

Ha: 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.

Ha: 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.

Ha: 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.

Ha: 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.

Ha: 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.

Ha: 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.

Ha: 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

Ha: 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

Ha: 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.

Ha: 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.

Ha: 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.

Ha: 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.

References