issn : 2454-9150 vol-06, issue-08, nov 2020 cross-cultural

International Journal for Research in Engineering Application & Management (IJREAM)

ISSN : 2454-9150 Vol-06, Issue-08, NOV 2020

112 | IJREAMV06I0868028 DOI : 10.35291/2454-9150.2020.0686 © 2020, IJREAM All Rights Reserved.

Cross-Cultural Variations Affects on Employees

Competitiveness, Motivation, Attitude and Work

Environment Shipra* and Prof. (Dr.) Gurcharan Singh Ghotra**

*Ph.D Research Scholar, **Professor Department of Economics and Management, RIMT

University, Mandi Gobindgarh, Punjab, India.

Abstract - Motivation and work culture plays a very important role in determining the productivity and production of

any organization domestic or multinational corporation. Work culture therefore have the potential/capabilities to

increase or elevate the performance of the managers of organization. The purpose of the present research paper was to

examine the role of motivation, work culture and work environment prevailing in an industry/organization with

employees coming from diverse cultural background – both internal and external cross-cultural variations. The

purpose was also to investigate how far motivation or demotivation of employees working in a cross-cultural

environment (both internal and external) had positively or adversely affected the productivity, efficiency and

competitiveness and work environment, attitude, work culture of an organization/industry under the study. The

equally important objective of the study was to establish or determine whether the external cross-cultural variations

had a positive or a negative affective on the motivation, work environment, attitude, coordination, communication and

leadership of the technical employees working within the organization. The study also attempted to investigate whether

internal and external cross-cultural variations led to work conflicts, work tension, stress, among employees and how the

work production and productivity was affected as a result of prevailing of such situations in organization/industry. The

three main objectives which were studied under the present paper included: (i) To study the positive and negative

affects (if any) caused by the Cross-Cultural Variations, on the employees Motivation. (ii) To determine/ evaluate, how

the work environment, work culture, Motivation, (Values and Attitude) has changed in the organization, due to the

Cross-Cultural Variations. (iii) To Measure, the Competitiveness which has been noticed in the organization /industry

due to Cross-Cultural Variations. Beside of the above two hypotheses were also set and tested i.e (Null and Alternative

hypotheses). Various statistical tools used to test the hypotheses were mean, standard deviation, t-test, correlation, One

Way ANOVA, Regression Analysis and Factor Analysis. The findings of the study pointed out that when employees

were satisfied, and retreated with full dignity and their work performance and felt that their superiors or people

coming from foreign countries provided them with support and motivation or inspiration their contextual performance

increased to a great level there were no work conflicts prevailing in the organization with the internal technical and

non-technical and external technical employees coming from foreign countries an working in the organization.

Keywords: Motivation, work environment, attitude, work conflicts, production and productivity, leadership.

I. INTRODUCTION

The present paper attempts to examine affects of cross-

cultural variations on employees competitiveness,

motivation, attitude and work environment in the

organization under the study. Several studies had been

conducted on the motivation of employees, competitiveness

and work environment before the undertaking this study.

Studies on motivation carried out included Panying and

Binglu Zhao (2017), Farideh Salili (1996), Yamauchi

Hirotsugu, Dov, Elizur et al, (1996), Fey F. Carl (2005),

Ayan Zeynep et al, (2014) concluded that employees

motivation in cross-cultural variations situations prevailing

in organization increased rather than decreasing. Employees

felt highly motivated and competitive in working in a cross-

cultural environment. In the similar way studies carried out

on competitiveness, employees attitude, work environment

and work conflicts also provided diverse observations about

prevailing conflict as a result of existing/prevailing cross-




cultural variations in an organization. The studies included

Al Jenaibi (2011) Greblikaite & Devgeline (2010), Visagie,

J.C. and Linde, H.M. (2011), Ya Fang Trar (2011), Amah

Edwinah (2012), Kawar T.I. (2012), Elasaid Abdel (2012)

all such studies were carried out by using primary and

secondary data. The studies used various statistical methods

to measure to competitiveness, motivation, work culture,

work environment, attitude and conflicts among the

employees. The present study by taking into consideration

therefore made and attempt to study employees

competitiveness, motivation, attitude and work environment

in an organization by taking into consideration the

prevalence of cross-cultural variations.

1.1 Culture and work culture:

Culture had and impact positive or adverse on the

performance of employees, work conflicts, motivation,

work culture and work environment an pointed out by

various studies carried out by various scholars on the

subject. Culture and work culture played dominant role in

measuring the employees competitiveness, motivation,

work culture and work environment for example scholar

such as (Hofstede, 1980), Ouchi 1981 Hofstede and Bond

1988, Kotter and Heskette, 1992, Magee, 2002) claimed

that the organizational culture helped to provide

opportunity and broad structure for the development of

human resources, Technical and behavioral skills in an

organization which covered work and work conflicts

attitude, motivation, work environment.

1.2 Objectives The present research paper as mentioned

above attempts to cover the following three main

objectives (i) to Measure, the competitiveness which has

been noticed in the organization/industry due to cross-

cultural variations (ii) to study the positive and negative

affects (if any) caused by the cross-cultural variations, on

the employees motivation (iii) to determine/evaluate, how

the work environment, work culture, motivation, (values

and attitude) has changed in the organization, due to the

cross-cultural variations.

1.3 Hypotheses

The present research paper studied the above objectives and

by setting the two hypotheses to test the various variables

(competitiveness, motivation, attitude work conflicts and

work culture) whether they had any significant affect on

employees competitiveness, motivation, work culture,

attitude, work environment and conflicts etc.

II. LITERATURE REVIEW

Faradeh Salili (1996) The research study explored the

relationship between age, sex and cultural differences in

achieving motivation. The total sample covered under the

study was 764 male and female British high school and

Chinese students age 13-55. The study applied or used the

thematic apperception test (TAT) to measure the need for

achievement of (nach). Results of the study revealed that

Chinese high school students had significantly higher

(nach) scores that their British counterparts. It was also

observed by the study that they also had a significantly

higher scores them their two older groups of Chinese

students. The further revealization of the study pointed out

that the female subjects of both culture had higher score

than males, although this difference was significant for

British female subjects only. The results of the study were

discussed in terms of socio cultural and situational factors.

Yamanchi Hirotsugu, Dov, Elizun et al (1996) In its

research study pointed out that an international research

projects on achievement of motivation was originated based

on a multifaceted approach. The main objective of the study

was to examine the structure of the achievement motive

domain for samples from five countries such as the United

States, the Netherlands, Israel, Hungry and Japan. They

study hypothesized that data collected from the various

samples reflected the basic features suggested by the

definitional frame work of achieving motivation. Results

from 1868 respondents supported the hypothesis tested by

the study that the individualistic and collectivistic cultural

orientations will have an effect on motive strength as well

as motivation. The three basic features of the definition of

achievement motive such as (i) behavior modality (ii) type

of confrontation and (iii) time perspective relative to task

performance were reflected as major determinants of the

data. Achievement tendencies in case of motivation were

found to be higher for USA respondents and lowest for the

Japanese and the Hungarian respondents. The study

suggested the theoretical implications for conducting

further research on the subject mentioned by using

quantitative analysis.

Fay F. Carl (2005) the study made an attempt to examine

the factors (or the similar factors) which motivated the

middle class managers in Sweden and Russia. The study

was based on the sample of 82 Swedish managers and 86

Russian managers. The hypotheses were set using the

main/key understanding of natural cultural differences and

several popular theories of motivation the need theory,

equality theory, goal setting theory, and the feedback

theory. The empirical analysis of the study and the results

obtained showed that natural culture plays an important role

in determining what motivates people. Russian and

Swedish manages were arguably motivated by different

factors such as perks, need hierarchy and the work

environment. The results provided strong support for needs

hierarchy theory. Swedish managers were highly motivated

by perceived equality with their peers.

Inder Science (2010) carried out on indepth analysis of the

nature of organization ethos prevalent in different sectors of

India economy by taking the profile of octapace. Data was

collected from the employees of 16 different organisatioins,

belonging to the consulting, manufacturing services and




IT/IJES Sectors. Analysis of the data pointed out that there

existed significant differences in the culture of the

organizations under the study. Analysis further pointed out

that all then to city and autonomy were more priced/ valued

in consulting as compared to the manufacturing and

services Industry. Openness and confrontation were higher

in the IT/ITES sectors, while collaborations were higher in

the manufacturing sectors. Furthermore, Private sectors had

an open and trusting culture, as compared to, the Public

Sector. Results of the study further pointed out that

employees, who were professionally qualified rated

confrontations, authenticity and autonomy higher than

those, who were not professionally qualified. However, no

significant differences existed between males and females

in evaluation of organizational culture. The study used t-test

to find out the significant differences between population

means (2-sample), t-values measured, the size of the

difference relative to the variations in the sample data.

Al Jenaibi (2011) Argued that managing workplace

diversity became the main concern among organizations in

today. The United Arab Emirate (UAE), one of the World’s

largest net migration rates, and the number of workers from

India, the Philippines, Indonesia, Australia, the USA among

other countries increased significantly in the recent decades.

The UAE cross border mobility resulted in the interaction

of people, with diverse languages, cultures and ethanic

backgrounds, due to, the nature of the UAE work force,

which was dominated by foreign workforce. The study

therefore, critically analyzed the benefit and challenges,

which the organizations faced in the diverse work place of

the UAE. The study used a multi method approach

combining survey data from 750 surveys of foreign workers

with quantitative data from interviews, with native officials

of the organization. The research found generally a

favorable view towards workplace diversity, from the

perspective of surveyed employees. However, when asked

about more detailed questions about the company’s policy,

a significant segment of respondents expressed

reservations, about their employees ability, to implement

successful intercultural communications and diversity

practices.

Visagie, J.C and Linde, H.M. (2011) Expressed the

relationship between the employees perceptions of

organizational culture in a multinational construction

company and concluded that, if an organization/Industry

developed and maintained a supportive and applied work

culture, it would lead to higher performance, by including

high competitiveness, diversified work conditions, and

short period of work written a specified team of people.

Working conditions were mainly formed in high safety risk

environment and sometimes less than living conditions,

where people were working. The employees, who worked

in a flexible atmosphere were likely to be more discrete.

This type of organization was observed to be more

supportive to employees and in development of work

culture.

Amah Edwinah (2012) examined empirically the affects of

corporate culture on employees job performance, as well as,

organizational productivity, and effectiveness by making

the case study of the Nigerian Banking Industry. A total of

388 managers were randomly drawn from a population of

13339 managers of all the 24 Banks in Nigeria the

instruments used were the questionnaire and the oral

interviews Spearman’s Rank correlation statistical tool was

used to test the hypothesis the findings pointed out that

adaptability positively influenced the organizational

profitability and market share. It was further observed that

there was no significant relationship between adaptability

and organization productivity. The finding of the study,

pointed out that a good large number of respondents (57.7

percent) strongly agreed that Corporate culture had or did

effect positively on the employees job performance.

Employees performance did show improvement, and

another 48.7 percent of the employees, also agreed that the

corporate culture determined the productivity level of the

organization, as well as, of the employees. There findings

made up to accept the alternative hypothesis because in

both the cases the calculated value of chi-square were found

to be greater than the tabulated values.

Beyond doubt, todays organizations had become

predominantly dynamic in nature and such organizations,

enveloped large opportunities and challenges, to the

corporate practitioners and policy makers. In the past, there

had been researches in literature to explore the effect of

organizational culture on various human development

programmes of an organization. For example scholars such

as (Hofstade, 1980), Ouchi 1981 Hofstede and Bond 1988,

kotter and Heskette, 1992, Magee, 2002) claimed that the

organizational culture helped to provide opportunity and

broad structure for the development of human resources,

Technical and behavioral skills in an organization.

The purpose of the research paper was to; explore the

impact of organizational culture on Productivity and quality

in Software organization in case of India. This empirical

study was done basically in two phases. The first phase

adopted Qualitative Methodology and explored the

significant aspects of organizational culture such as

productivity and quality and nature of relationship

organizational culture had with productivity and quality.

The second phase made a qualitative analysis of this

relationship. The study developed a large a range of insights

into the way the cultural processes, tended to, influence

productivity and quality in people centric and knowledge

intensive work contexts such as software’s. The study also

employed perceptual measures of productivity and quality

in carrying out the quantitative analysis.

Kawar T.I. (2012), in its research article studied the cross-

cultural differences in management. The study pointed that




there are areas in management, whereby differences

towards attitudes behaviours, functioning, communication

issues and cultural implications can be seen. Cross-cultural

differences mainly stemmed from the different background

of each culture. Cultural varieties could be witnessed in the

work place and other factors introduced other than the

factors mentioned above included sales target, meeting

deadlines, working on tight budgets which could lead to

cause work conflicts. Because the differences in culture

may occur that could lead to misunderstanding among

people working in the same organization due to their

different values, beliefs, background etc. The study

concluded that the successful management of any person

would lie in his capability to work with people from

different cultural backgrounds, no matter what their cultural

was orientation. It further pointed out that an evidence on

this was the successful management of many Western

companies operating in different parts of the world such as

Middle East and they come with good managerial results,

the study concluded.

Ya Fang Trar (2011) emphasized on the fact that

organizational culture referred to the beliefs and values that

had existed in, an organization for a long period of time and

to the belief of the staff and the foreseen value of their work

that influenced their attitude and behavior. Administrators

and Managers usually were found to be adjusting their

leadership behavior, to accomplish the mission, of the

organization and this could influence, the employees job

satisfaction. It was, therefore, essential to, understand the

relationship between organizational culture, leadership

behavior and job satisfaction of the employees. In this

context, a cross-sectional study was undertaken that focused

on the hospitals and nurses in Taiwan. Data were collected,

using a well-structured questionnaire. 300 questionnaires

were distributed and 200 valid questionnaires were received

or returned by the respondents. To test the reliability of the

data, they were analysed by cross-bach’s and the

confirmatory factors. Correlation analysis was used, on the

relationship between organizational cultures leadership

behavior and job satisfaction. Organizational cultures were

significantly (positively) correlated, with the leadership

behavior and job satisfaction and leadership behavior was

significantly (positively) correlated with job satisfaction.

Aycan Zeynep et al (2014) basically reviewed the research

on cross-cultural organizational behavior (OB). The study

broadly construed, cross-cultural organizational behaviour

as the study of the cross-cultural organizational behavior as

the study of the cross-cultural similarities and differences in

process and behavior at work and the dynamics of cross-

cultural interfaces in multi-cultural domestic and

international contexts. The study is based on the review of

more than 1000 publications on cross-cultural variations

and organizational behavior. The review showed that

developmentally, cross-cultural research in OB was coming

of aged as the study clearly pointed out how individuals

manage, their interdependence in organizations and

reviewed research on culture and negotiations and disputing

teams and leadership, followed by research on managing

across borders and expatriation. The study highlighted

critical challenges for future research which

included/enveloped moving beyond values to explain

cultural differences, attending focusing or concentrating to

levels of analysis issues, incorporating social and

organization context/text factors into cross-cultural research

and work culture, work environment.

Panying and Binglu Zhoo (2017) stated that modern day

work culture of various organization changed to a great deal

as more and more employees emanated from not only from

different countries but regions were observed to be marking

in the domestic and international companies and how to

motivate employees working together in such organisations.

It was a very important issue to study or explore. The

present study made together a lot of existing research

results with the actual business operation situations, the

present research paper is based on pure theoretical analysis

of various theories on motivation. Based on the research

results of scholars at home and abroad the study discussed

the incentives for cross-cultural employees in international

enterprises from four aspects which were significant of

work hierarchy of needs and dichotomy of internal and

external factors as well as the reward and punishment

mechanism. It was observed that the characteristics and

mechanism of effective incentives of different cultures were

different.

Jassy Mathew (2019) evaluated vertically the theorized

relationship between organizational culture and

effectiveness. The study was based on the empirical data

collected through a five-month ethnographic study in an

Indian knowledge intensive firm. It used/followed the three-

perspectives framework of culture that, enveloped

integration, differentiated and fragmented perspectives and

a comprehensive examination of effectiveness. The study

concluded that integrated, differentiated and frequentative

perspectives of culture, capture multiple organizational

values and they affect, effectiveness in varied ways.

Appropriate culture, although not sufficient conditions were

crucial for effectiveness, especially in knowledge intensive

firms. High level of differentiation and frequentative

prevent the formation of strong culture, which challenged

organization integration. There was heightened need for the

application of sophisticated Human Resource Management

(HRM) systems in the Indian Software Sector. (Bryan,

1999) In concrete terms cultural diversity in the work place

is which he considered was exercised through the co-

existence of workers, who came from different

backgrounds. The management of cultural diversity

required, therefore, a type of organizational culture, in

which, every employees career was not affected by age,

gender, race, religion or other factors not related to

performance.




III. RESEARCH METHODOLOGY

The present study was conducted by following stratified

random sampling technique.

Shreyans Industries Limited, Ahmedgarh District Sangrur,

Punjab got selected where both the internal and external

cross-cultural variations existed. The present research paper

studied the three objectives mentioned above

(competitiveness, motivation, work culture and work

environment etc.) with the help of secondary data collected

from Shreyans Industries Limited, Ahmedgar, Sangrur,

Punjab.

1.5 Data Collection

Data were collected from primary as well as secondary

sources. Secondary data was collected from the Head office

of Shreyans Industries Limited, Ahmedgarh, District

Sangrur, Punjab. Objective-I of the study was examined

with the help of secondary data analysis. The objective-II

and III were studied with the help of sampled primary data

collected from the technical and non-technical employees

of Shreyans Industries Limited as discussed below:

1.6 Secondary Data Analysis Techniques

The data analysis techniques used for studying the

motivation, competitiveness, work culture and work

environment, work conflicts, attitude etc. included (i) trend

analysis (ii) Chi-square test and other statistical tests as can

be seen from the analysis of secondary data given below:

1.6.1 Secondary data analysis and results

In order to study the sense of the competitiveness secondary

as well as primary data collected from Shreyans Industries

Limited were analyzed and the results were presented as

below:

OBJECTIVE-I: TO MEASURE THE

COMPETITIVENESS WHICH HAS BEEN NOTICED

IN THE ORGANIZATION/INDUSTRY DUE TO

CROSS-CULTURAL VARIATIONS

A) Production: Table 1 given below provides year-wise

data for the years 1982-83 to 2017-18 on the total

production in millions, cost of production in Rs.(millions)

and profits in millions Rs. In case of Shreyans Industries

Limited, Ahmedgarh, Punjab.

Since the time series data was available for a large number

of years since 1982-83 to 2017-18 trend analysis was

carried out to find out the trend in production, cost and

profits. In case of production it showed that R2 value was

0.98 which was quite/highly significant, whereas, the F-

value was found to be (F=1433.7) which was also found to

be significant at (0.01) level of significance. This showed

that the production of paper in the Industry, since 1982-83

had been on the rise, till the year 2017-18. From the b co-

efficient value (b-1203.70), p<0.01) which showed that

production increased by amount of Rs.1203.7 and found to

be statically significant at 0.01 level. The results of the

same were presented by way of graph given in figure 1.

B) Costs: Year wise trend analysis was carried out on

production was also applied on the cost of production. It

was observed that, the year-wise trends in case of year-wise

cost that also observed to rising and the Ads R2 value was

0.98, which was again highly significant, whereas the F

value (1566.3), which was again observed to be significant

at 0.01 significant level. This showed that year-wise cost

was changing and varying from the year 1982-83 to 2017-

18, but overall was rising. From the co-efficient value (b

=1210.1, p<0.01), which showed that cost increased by

amount of Rs.12101 and found to be significant at 0.01

level.

C) Profits: In the similar way, the year-wise trend in profits

were obtained. It can be seen from the table 1, and figure 3

which provided year-wise trend of profits. In case of

profits, again check adj. R2 value was found to be 0.98,

which was highly significant, and the F value was found to

be F=1635.4 which again was significance at 0.01 level of

significant. This showed that the profits are varying or

changing since 1982-83 to 2017-18. It was further noted

from the results that beta co-efficient value (b=1006.5,

p<0.01) which showed that he profits increased by amount

of 1210 and found to be significant. The presented study

therefore evaluated the affects of cross-cultural variations

on production employees productivity, efficiency and sense

of competitiveness in Shreyans Industries Limited

Ahmedgarh, Punjab, India. The study also pointed out and

firmly laid emphasis, on the internal cross-cultural

variations, which existed in the organization and which to a

great extent also affected the production, cost, profits,

employees productivity, efficiency etc. The present study,

therefore, analysed or examined two types of cross-cultural

variations by taking into consideration the definition of

culture stated in (Chapter-I). External cross-cultural

variations (mainly foreign employees/experts working, with

local employees) and ii) Internal cross-cultural variations-

where employees, belonging to different domestic

Nationalities (different states) worked together and how

such internal cross-cultural variations and external cross-

cultural variations affected employees productivity,

efficiency, competitiveness work environment, motivation

(positively or adversely) etc. were analysed and presented.

This chapter, on data analysis on cross-cultural variations

(both internal and external) mainly dealt with the data

collected and analysed mainly from the secondary sources

i.e. the Head office and technical department and

production departments etc. as well as from the different

departments such as data on production, exports and

imports, costs and profits, raw material used (chemicals and

fuel) number of employees (both technical and non-

technical) and data on infrastructure such as power, water,




transport etc. The secondary data thus collected was

analysed and the results were presented.

Table 1: Year wise production, cost and profits of

Industry

Year Production

(million

(Rs)

Cost

(in million Rs)

Profits

(in million Rs)

1982-83 3523 5989 2466

1983-84 6597 11215 4618

1984-85 8157 13867 5710

1985-86 9471 16101 6630

1986-87 10276 17469 7193

1987-88 11619 19752 8133

1988-89 12434 51138 8704

1989-90 11009 18715 7706

1990-91 14188 24120 9932

1991-92 14581 24788 10207

1992-93 19164 32579 13415

1993-94 21185 36015 14830

1994-95 22442 38151 15709

1995-96 22647 39632 16985

1996-97 22332 40198 17866

1997-98 24964 44935 1997

1998-99 25899 46618 20719

1999-20 28623 51521 22898

2000-01 29356 52841 23485

2001-02 29341 52814 23473

2002-03 29952 53914 23962

2003-04 29214 52585 23371

2004-05 29527 53149 23622

2005-06 33565 60417 26852

2006-07 33287 59917 26630

2007-08 33796 60833 27037

2008-09 34022 61240 27218

2009-10 34729 62512 27783

2010-11 35702 64264 28562

2010-12 36578 65840 29262

2012-13 44875 80775 25900

2013-14 45350 81630 36280

2014-15 43307 77953 34646

2015-16 45873 82571 36698

2016-17 48601 87482 38881

2017-18 49169 88504 39335

R2 0.98 0.98 0.99

Adj R2 0.98 0.98 0.98

F value 1433.7

(<0.01)

1566.3(<0.01) 1635.4(<0.01)

Beta coefficient

(b)

1203.7 2210.1 1006.5

Std.Error 31.8 55.84 24.9

t value 37.9 39.58 40.4

p value <0.01 <0.01 <0.01

Source: Secondary data collected from Head Office

Shreyans Industries Limited-2017-18.

Fig. 1(a): Year wise production of Industry

R2 value is 0.98 and significant value F=1566.3, which is significant at 0.01 level of significance. This shows production is

significant vary from year 1982-83 and 2017-18. From beta coefficient value (=1203, p<0.01), which shows, production is

increase with amount 1203.7 and found significant at 0.01 level.

0

10000

20000

30000

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50000

60000

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82-8

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Production (million (Rs)




Fig. 1(b): Year wise cost of Industry


significant vary from year 1982-83 and 2017-18. From beta coefficient value (=1210.1, p<0.01), which shows, production is


Fig. 1(c): Year wise profit of Industry


significant vary from year 1982-83 and 2017-18. From beta coefficient value (=1006.5, p<0.01), which shows, production is


Table 2: Effects of Production and Cost of Production from 1982-83 to 2017-18.

Beta coefficient Newey-West Std.

Err.

t-value p-value 95% Confidence Interval

Minimum Maximum

Constant -1602.9 258.4 -6.20 0.00 -2158 -1077

Production 1.82 0.01 196.2 0.00 1.80 1.84

a. Dependent variable: Costs

b. Based on secondary data.

Table 2 above represented the regression result obtained/worked out by using Newey-West std. Error, where the dependent

variable used was the cost, and the independent variable used was the production. Significant linear relationship (F=7814,

p<0.01) was observed between dependent and independent variable at (0.01) level of significance. It was further observed that

the costs increased with increase of production (=1.82) and this increase was found to be statistically significant (t=196,

p<0.01) at 0.01 level of significance.

0

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20000

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-83

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2

20

12-1

3

20

13-1

4

20

14-1

5

20

15-1

6

20

16-1

7

20

17-1

8

Cost (in million Rs)

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

19

82-8

3

19

83-8

4

19

84-8

5

19

85-8

6

19

86-8

7

19

87-8

8

19

88-8

9

19

89-9

0

19

90-9

1

19

91-9

2

19

92-9

3

19

93-9

4

19

94-9

5

19

95-9

6

19

96-9

7

19

97-9

8

19

98-9

9

19

99-2

0

20

00-0

1

20

01-0

2

20

02-0

3

20

03-0

4

20

04-0

5

20

05-0

6

20

06-0

7

20

07-0

8

20

08-0

9

20

09-1

0

20

10-1

1

20

10-1

2

20

12-1

3

20

13-1

4

20

14-1

5

20

15-1

6

20

16-1

7

20

17-1

8

Profits (in million Rs)




Table 3: Effects of Production vs. Profits of Industry from 1982-83 to 2017-18.

Beta coefficient Newey-West Std.

Err.

t-value p-value 95% Confidence Interval

Minimum Maximum

Constant -1602.9 258.4 -6.20 0.00 -2158 -1077

Production 0.82 0.01 88.4 0.00 0.80 0.84

a. Dependent variable: Costs

b. Based on secondary data.

Table 3 gave provided the regression results, with Newey-West Std. Error. In this case, the dependent variable used was Profits

and independent variable used was production. Significant linear relationship (F=7814, p<0.01) was observed between

dependent and independent variable at (0.01) level of significance. It was further observed from the table that profits increased

with the increase in production (=0.82) and the increase was found to be statistically significant as (t=88.4, p<0.01) at 0.01

level of significance.

Table 4: Total Exports Vs. Imports Behaviour (2008-2018)

Year Imports

(in million tons)

Exports

(in million tons)

2008-2009 107864 14559805

2009-2010 98739 5700581

2010-2011 117762 59951701

2011-2012 121534 85170622

2012-2013 125167 68817981

2013-2014 141629 60051090

2014-2015 143248 31343967

2015-2016 146395 23284784

2016-2017 35780 33534748

2017-2018 158250 140691644

R2 85.3 19.9

AdjR2 83.3 9.9

F value 46.5 1.99

Beta coefficient 5682 5916753

Std. Error 833.2 4196745

t value 6.82 1.41

p value <0.01 0.20 (ns)

Source: Secondary data collected from Head Office Shreyans Industries Limited-2017-18.

From the table above, it can be observed that R2 value is 85.3% and F=46.5, and 1.99 whereas the Ads R2 value was 83.5

which were significant at (0.01) level of significance. This showed that Imports played a very important role and were

increasing from 2008-2009 to 2017-2018. From beta coefficient value (=5682, p<0.01), it can be further observed that

imports increased by amount of Rs.5682 every year and were found to be significant at (0.01) level as shown in Fig 2 from

table it can also be observed from that in case of imports R2 value was 85.3 and F-value and the Adj R2 value was 83.5 and

which were significant at (0.01) level of significance. This also showed that imports played a very important role and were

increasing since 2008-2018. Hence imports showed a very significant role. From beta co-efficient value (=5682, p<0.01), it

was further observed that imports increased by amount 5682 every year and were found to be significant at 0.01) as shown in

Fig. 2.

In the same way. In case of Exports, R2 value was 19.9% and Adj R2 value was 9.9 and the F value was 1.99, which showed

that it was non-significant. However, year-wise trends of Exports, at 0.05 level were found to be significance as shown in fig.

2. This significance level in exports showed, that. This could be due to be some data errors. However, the presented study

recommended that this phenomenon needed further study and investigation.




Fig. 2: Total Exports Vs. Imports Behaviour (2008-2018)

Linear Regression: It was observed from the previous analysis that Employees Productivity and Employees Efficiency was

influenced by the Market Competitiveness (i.e. Imports and Exports) from the Shreyans Industries Limited. Linear Regression

Analysis was carried out to asses, the impact of market competitiveness in enhancing Employees Productivity and Efficiency

and the results obtained in this regard were presented in table 5 below:

Table 5: Employees productivity and efficiency

Fact R2 Constant Regression Co-efficient t-value f-value

Employees productivity

Import-MT 0.483 45.511 0.006 2.731 0.026

Import Rs 0.512 48.3737 0.000000203 2.900 0.020

Export-MT 0.068 58.87 0.002 0.764 0.467

Export(Rs) 0.164 57.8 0.00000068 1.250 0.246

Employees Efficiency

Import-TM 0.481 18.142 0.002 2.722 0.026

Import Rs 0.509 19.303 0.000004841 2.880 0.021

Exports-MT 0.071 23.499 0.001 0.783 0.456

Exports(Rs) 0.168 23.072 0.000000281 1.270 0.240


The above analysis clearly indicated that the levels of imports and exports had a significant impact on Employees Productivity

and Efficiency in Shreyans Industries Limited. Cross-Cultural Variations (both Internal and External) brought over the period

1978-2018 sense of Competitiveness among the employees, Quality of paper Production has increased (which has not only led

to higher production, but also in the increase of Exports) higher wages, incentives and increments. In the analysis presented in

the above table, it was further observed that with regard to employees productivity, the value of R2 (Co-efficient of Multiple

Determination) came to 0.483 and 0.512 in case of imports in physical terms and value terms in which further revealed that

48.3 and 51.2 percent variations in the Employees productivity were found due to the variations in the levels of Imports in

physical as well as value terms respectively. The value of Regression co-efficients indicated that there was a little

improvements i.e. only (0.006) and (0.000000203) times with one unit increase in the level of Imports, both in physical as well

as, in value terms. In the same way in case of Exports, the employees productivity the value of R2 was observed to be 0.68 and

0.164 in physical terms and in value terms, which further revealed that 68% and 16.4% variations in employees productivity

were due to the variations in the levels of exports in physical as well as in value terms. The values of regression co-efficient

showed that there was a little improvement i.e. (0.002) and (0.00000068) times with one unit increase in the level of exports

both in case of physical as well as value terms. The Contribution of Exports towards in the recent years showed a slight

0

20000000

40000000

60000000

80000000

100000000

120000000

140000000

160000000

2008-2009 2009-2010 2010-2011 2011-2012 2012-2013 2013-2014 2014-2015 2015-2016 2016-2017 2017-2018

107864 98739 117762 121534 125167 141629 143248 146395 35780 158250

145598055700581

59951701

85170622

6881798160051090

3134396723284784

33534748

140691644

Imports (in million tons) Exports (in million tons)




Decline due to technical and data errors reporting. This observation was further investigated with the help of primary data

collected which showed that Secondary data compiled on Exports and imports was erratic and not correctly recorded/revealed.

The analysis of Primary data had shown a clear increasing trend in the Exports and Imports behaviour in case of Shreyans

Industries Limited. The results of the Primary data were presented in chapter on primary data analysis.

Similarly, in the case of the Employees efficiency, the value of R2 (Co-efficient of multiple determination) came out be 0.481

and 0.509 in case of Imports in Physical terms and value terms which clearly revealed that 48.1 and 59.1 per cent in the

employees productivity were, due to the variations, in the levels of Imports in Physical as well as in value terms respectively.

Once again, it was observed from the table that the value of the Regression Co-efficients indicated that there was a very little

Improvements i.e. only (0.002) and (0.000000481) times, with one unit increase in the levels of Imports, both in Physical, as

well as, in value terms. In the similar way in case of employees efficiency, the value of R2 was observed to be 0.071 and

0.168, in case of exports, in physical and value terms, which further revealed that 71% and 16.8% variations in employees

efficiency were, due to the variations in the levels of experts in physical as well as, in value terms. The values of regression co-

efficients did showing a very small/little improvements i.e. (0.0011 and 0.000000281) times, with one unit increase in the level

of Exports both in case of physical, as well as, value terms. In the similar way, again like-wise in case of Employees

Productivity, the contribution of Exports towards Employees Competitiveness came out to be Statistically Non-Significant, due

to occurrence of data errors (erratic data) gathered from the Secondary sources. However, the analysis of Primary data. Cleary

pointed out that the sense of competitions prevailed in the Industry or organization.

The Regression Analysis carried out above thus brought out, that the level of the Imports significantly improved the

Employees sense of Competitiveness, while the contribution of Exports towards the Employees productivity and efficiency and

Competitiveness remained Non-significant as far as the results of secondary data revealed.

Graphically figure 1 below provides the status of Employment. Employees productivity, employees efficiency and imports and

Exports.

Table 6: Year wise total prices and quantity of materials, chemicals and fuel prices

Year

Chemical Material Fuel

Price Quantity Price Quantity Price Quantity

2008-09 19438 68094 63501 36464 72445 3306

2009-10 18277 61839 58843 33703 67284 3197

2010-11 20699 67148 60646 46876 72659 3738

2011-12 23900 72816 67287 44614 71621 4104

2012-13 27381 80805 80354 39908 73771 4454

2013-14 30312 84599 83377 52570 91686 4460

2014-15 27637 86338 72318 52160 71689 4750

2015-16 31059 88185 77245 54070 81292 4140

2016-17 32090 87675 85506 45025 85038 3080

2017-18 35927 100300 86641 54080 91087 3870

R2 96 94.3 88.6 76.6 72.2 26.6

ADJ R2 92 88.9 78.4 58.6 52.2 7.1

F value 81.7 55.88 25.4 9.92 7.64 0.53

Beta coefficient 2197.5 4365.5 3512.9 2106.1 2419.4 55.2

Std. Error 243.0 583.9 696.4 668.6 875.1 76.7

t value 9.04 7.47 5.40 3.15 2.76 0.73

p value <0.01 <0.01 <0.01 <0.05 <0.03 0.49(ns)


Year wise total prices and quantity of materials, chemicals and fuel prices for the years 2008-09 to 2017-18 was collected from

the secondary sources i.e the head office of the Industry. The same data has been analyzed and the results of the data analysis

showed adjusted R2 value, F-value, Beta coefficient, Std. error, t-value and p-value. The same data was presented in terms of

the trends analysis of Fig. 3(a) price of chemicals, Fig. 3(b), quantity of Chemicals, Fig. 3(c), price materials, Fig. 3(d),

quantity of Materials, Fig. 3(e), price fuels, Fig. 3(f), quantity of fuels given below:




Fig. 3(a): Trends of price of chemicals

Fig. 3(b)Trends of quantity of Chemicals

Fig. 3(c): Trends of price materials

y = 2197.x + 15606

R² = 0.921

0

5000

10000

15000

20000

25000

30000

35000

40000

2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18

Price of Chemical

y = 4365.x + 57839

R² = 0.888

0

20000

40000

60000

80000

100000

120000

2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18

Quantity of Chemical

y = 3513.x + 55253

R² = 0.784

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18

Price of Material




Fig. 3(d): Trends of quantity of Material

Fig. 3(e): Trends of price fuels

Fig. 3(f): Trends of quantity of fuels

y = 2106.x + 36088

R² = 0.586

0

10000

20000

30000

40000

50000

60000

2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18

Quantity of Material

y = 2419.x + 66214

R² = 0.522

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18

Price of Fuel

y = 55.91x + 3569

R² = 0.070

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18

Quantity of Fuel




Table 7: Total imports and exports

Years Imports Exports

2008-09 107864 14579805

2009-10 98739 5700581

2010-11 117762 59951701

2011-12 121534 85170622

2012-13 125167 68817981

2013-14 141629 60051090

2014-15 143248 31343967

2015-16 146395 23284784

2016-17 135780 33534748

2017-18 158250 140691644

R2 85.3 19.9

ADJ R2 83.5 9.9

F value 46.5 1.99

Beta coefficient 5682 5916753

Std. Error 833.2 4196745

t value 6.82 1.41

p value <0.01 0.20(ns)


Exports-imports behaviour Table 7 provided details about the behaviour of exports and imports from the Industry or

organization under the study for the year 2008-09 to 2017-18 and data analysis showed adjusted R2 value, p-value, beta

coefficient, Std. error, t-value and p-value as shown in table the figures 4(a) Trends of imports and 4(b) trends of exports below

showed the trends in the behaviour of exports and imports over the year.

Fig. 7(a): Trends of imports

Fig. 7(b): Trends of exports

y = 5682x + 98386R² = 0.8532

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18

Imports (Rs.)

y = 6E+06x + 2E+07R² = 0.199

0

20000000

40000000

60000000

80000000

100000000

120000000

140000000

160000000

2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18

Exports (Rs.)




Table 8: Year wise exports sales for the year 2008-09 to 2017-18

Year Quantity (MT) Amount Mts Rate per MT

2008-09 354.748 14579805 41099.05

2009-10 170.521 5700581 33430.43

2010-11 1583.536 59951701 37859.38

2011-12 2132.882 85170622 39932.18

2012-13 1427.709 68817981 48201.69

2013-14 1132.528 60051090 53023.92

2014-15 622.169 31343967 50378.54

2015-16 493.481 23284784 47150.33

2016-17 642.710 33534748 52177.11

2017-18 2425.086 140691644 58015.12


Fig. 5: Year wise exports sales for the year 2008-09 to 2017-18.

Table 9: Raw materials domestic consumption and total exports

Years Production in

tones

Domestic

Consumption in

tones

Total Sale (in

Tones in

Rs/crores)

Domestic sale

within the

country (in

tones0

Total

Exports (in

tones)

Exports value in

US$ Dollars

2008 Paper 39400 800 38000 600 53400

Soda Ash 10500 0 10500 0 0

2009 Paper 40500 500 39500 500 490000

Soda Ash 11000 0 11000 0 0

2010 Paper 42500 400 41500 600 546000

Soda Ash 12000 0 12000 0 0

2011 Paper 43800 800 42000 1000 960000

Soda Ash 12500 0 12500 0 0

2012 Paper 43900 400 43000 500 539640

Soda Ash 13000 0 13000 0 0

2013 Paper 45800 800 44000 1000 1072343.51

Soda Ash 14000 0 14000 0 0

2014 Paper 45500 500 4400 1000 954108.3

Soda Ash 14000 0 14000 0 0

2015 Paper 44000 400 43000 600 524988.62

Soda Ash 13000 0 13000 0 0

2016 Paper 46600 600 45500 500 355820.39

Soda Ash 14000 0 14000 0 0

2017 Paper 49200 600 48000 600 506077.72

Soda Ash 17000 0 17000 0 0

2018 Paper 51000 1000 49500 500 708087.72

Soda Ash 19000 0 19000 0 0


0

500

1000

1500

2000

2500

3000

2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18

Exp

ort

s in

me

tric

to

ne

s

Year

On the basis of this data show trend of Exports




Fig. 6: Raw materials domestic consumption and total exports.

OBJECTIVE-I: TO MEASURE THE COMPETITIVENESS WHICH HAS BEEN NOTICED IN THE

ORGANIZATION/INDUSTRY DUE TO CROSS-CULTURAL VARIATIONS

Objective-II: To study the positive and negative effects (if any) caused by the cross-cultural variations, on the

employees motivation.

Objective-III: To determine/evaluate, how the work environment, work culture, motivation, (values and attitude) has

changed in the organization, due to the cross-cultural variations

1.6.3 Technical employees: Competitiveness: Technical employee’s level of competitiveness was measured by a two periods

of time i.e 1978-79 to 1992-93 and (1993-94 to 2017-18). The technical employees competitiveness was measured by using the

primary data collected from the technical employees of the organization. The following two hypothesis were formulated and

tested.

i) Null Hypothesis (H0): Level of employees competitiveness in case of technical employees do not vary

significantly across two periods.

ii) Alternative Hypothesis (H1): Level of employees competitiveness in case of technical employees vary

significantly across two periods.

The status of employees competiveness in relation to cross cultural variations across two period of time is given in

Table 10. It was evident that, the proportion of technical employees, those reporting 'High competition of performance'

increased from 85.22 per cent in Period-I to 98.65 per cent in Period-II. The value of z-score corresponding to 'High

competition or/good competition and 'Average competition' came out to be greater than that of the critical level (2.576 at 1%:

1.96 at 5%), which further indicated that there were significant variations in employees competition in case of technical

employees across two point of time. Rather, the level of employees competitiveness in relation to cross cultural variations

across two period of time had improved significantly. The Null Hypothesis therefore stood rejected.

Table 10: Level of employees competitiveness in case of Technical Employees

Variables Period-I (1978-79 to 1991-92) Period-II (1993-94 to

2017-18)

Z-test Significance level

High competition 98 85.22 146 98.65 5.18 **

Good competition 8 6.96 1 0.68 2.78 **

Average competition 6 5.22 1 0.68 2.27 *

Some competition has begun 2 1.74 0 0.00 1.61 NS

No competition 1 0.87 0 0.00 1.14 NS

Source: Based on sampled primary data collected from the Shreyans Industries Limited-2017-18.

** and * significant at one and five per cent level of significance

39400

10500

40500

11000

42500

12000

43800

12500

43900

13000

45800

14000

45500

14000

44000

13000

46600

14000

49200

17000

51000

19000

0

10000

20000

30000

40000

50000

60000

Paper SodaAsh

Paper SodaAsh

Paper SodaAsh

Paper SodaAsh

Paper SodaAsh

Paper SodaAsh

Paper SodaAsh

Paper SodaAsh

Paper SodaAsh

Paper SodaAsh

Paper SodaAsh

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Year

Production in tones




Fig. 7: Level of employees’ competitiveness in case of Technical Employees (primary data analysis)

1.6.4 Association between competitiveness and level of employee’s productivity (chi square analysis)

Association between competitiveness and level of employees productivity was measured by applying the chi-square test. The

follow my two hypothesis were formulated and tested.

a) Null hypothesis (H0): There is no significant association between competitiveness and employees productivity.

b) Alternative hypothesis (H1) There is significant association between competitiveness and employees productivity.

The observed and expected frequency with respect to low and high level of employees productivity in relation to

competitiveness of technical employees was presented in Table 11. The results showed that the calculated value of chi-square

(17.595) was very high and the p-value was less than (0.01), which further showed that there was a significant association

between competitiveness and employees productivity. Therefore, the Null hypothesis stood rejected which revealed that the

level of employee[s productivity of technical employees vary significantly in relation to competitiveness of technical

employees as shown in the table 11 below:

Table 11: Association between technical employees competitiveness and level of productivity

Competitiveness Low (up to Rs 5603/hrs) High (>Rs 5603/hrs) Total

High competition performance Count 1 0 1

Expected count 0.4 0.6 1

Good competition Count 2 0 2


Average competition Count 6 1 7


Some competition has begun Count 8 1 9


Competition Count 98 146 244


Total Count 115 148 263

Expected count 115 148 263


Chi-square Test

Chi-Square Tests

Value df Asymp. Sign. (2-sided)

Pearson Chi-Square 17.595a 4 0.001

Likelihood Ratio 19.672 4 0.001

Linear-by-Linear Association 14.68 1 0

N of Valid Cases 263


a. 7 cells (70.0%) had expected count less than 5.

b. The minimum expected count is 0.4.

0

10

20

30

40

50

60

70

80

90

100

High competition Good competition Average competition Some competition hasbegun

No competition

85.22

6.96 5.221.74 0.87

98.65

0.68 0.68 0 0

Period-I Period-II




1.6.5 Association between competitiveness and employees efficiency-chi-square analysis.

Again under to find out the association between competitiveness and employees efficiency chi-square test was carried

out/applied. The following two hypothesis were formed and tested.

Null hypothesis (H0): There is no significant association between competitiveness and employees efficiency.

Alternative hypothesis (H1): There is significant association between competitiveness and employees efficiency.

The observed and expected frequency with respect to low and high level of employees efficiency in relation to competitiveness

of technical employees presented in Table 12. The results showed that the calculated value of chi-square (17.595) was very

high and the p-value was less than 0.01, therefore the null hypothesis stood rejected, which revealed that the level of

employees efficiency of technical employees vary significantly in relation to competitiveness of technical employees.

Table 12: Association between technical employees’ competitiveness and level of productivity

Employees productivity

Competitiveness Low (up to 89%) High (>89%) Total

High competition of performance Count 1 0 1


Good competition Count 2 0 2


Average competition Count 6 1 7


Some competition has begun Count 8 1 9


No Competition Count 98 146 244



Expected count 115 148 263


Chi-Square Tests

Value df Asymp. Sign. (2-sided)

Pearson Chi-Square 17.595a 4 0.001

Likelihood Ratio 19.672 4 0.001


No of Valid Cases 263

a. 7 cells (70.0%) have expected count has than 5.

b. The minimum expected count is 0.4.

1.6.6 Competitiveness among non-technical employees (based on primary data)

The status of employees competitiveness in relation to cross cultural variations across two period of time was tested by

developing following hypotheses:

Null Hypothesis (H0): Level of employees competitiveness in case of non-technical employees do not vary significantly

across two periods.

Alternative hypothesis (H1): Level of employees competitiveness in case of non-technical employees vary significantly

across two periods.

The status of employees’ competitiveness in relation to cross cultural variations across two period of time is given in Table 13.

It was evident from the table above that the proportion of non-technical employees, those reporting ''Excellent Competition'

increased from 24.32 per cent in Period-I to 55.68 per cent in Period-II. The value of z-score corresponding to 'excellent

competition' and 'some competition' came out to be greater than that of the critical level (2.576% at 1%: 1.96 at 5%), which

further indicated that, there were significant variations in the employees competition in the case of non-technical employees

across two point of time. Rather, the level of employees competitiveness in relation to cross cultural variations across two

period of time had improved significant. Therefore, the Null Hypothesis stood rejected.

Table 13: Sense of competition and competitiveness among non-technical employees

Particulars Period-I (1978-79 to 1991-92) Period-II (1991-92 to 2017-18) Z-test Significance level

Number Per cent Number Per cent

No Competition 2 5.41 9 5.11 0.07 NS

Some competition 6 16.22 9 5.11 2.40 *

Avg. competition 9 24.32 23 13.07 1.74 NS

Good competition 11 29.73 37 21.02 1.15 NS

Excellent competition 9 24.32 98 55.68 3.47 **





1.6.7 Association of efficiency level of employees with level of employees competition in the case of non-technical

employees of the organization (based on primary data)

Association between efficiency level of employees with level of employees competition in case of non-technical employees of

the organization –Chi Square analysis.

Chi square test was applied to test the following two hypothesis:

a) Null Hypothesis (H0): There is no significant association between efficiency level of employees with level of

employees competition in case of non-technical employees.

b) Alternative Hypothesis (H1): There is significant association between efficiency level of employees, with level of

employees competition, in case of non-technical employees.

The observed and expected frequency, with respect to low and high level of employees efficiency, in relation to

competitiveness of technical employees is presented in Table 14. The results showed that the calculated value of chi-square

(145.8) was very high and the p-value was less than 0.01, therefore the null hypothesis stood rejected, which revealed that, the

level of employees varied efficiency of non-technical employees varied significantly in relation to competitiveness of technical

employees. Therefore, the Null hypothesis was rejected.

Table 14: Different types of training programmes conducted

Competition

EFEF Level No competition Some competition Avg. competition Good Competition Excellent competition Total

Class Room Training 26 70.27 75 42.61 3.06 **

On job training 9 24.32 89 50.57 2.91 **

Off job Training 2 5.41 11 6.25 0.20 NS

Out of country on job

training

0 0.00 1 0.57 0.46 NS


OBJECTIVE-III: THE DETERMINE HOW THE WORK ENVIRONMENT HAS CHANGED IN THE

ORGANIZATION DUE TO CROSS CULTURAL VARIATIONS.

Table 15: Perception of technical employees regarding the various issue of working with other communities

S. No. Variables Number Percent

1. Working with other Indian nationalities 263 100.00

2. Work with all type of communities 263 100.00

3. Smooth working we are mixed with other communities (Teamwork) 263 100.00

4. Employees productivity is not negatively affected, while working with other communities 252 95.82

5. While working with other communities no conflicts occurred 263 100.00

6. There was no tension/no stress while working with other communities 263 100.0

7. The experience of working with other communities was motivating and not demotivating 263 100.00

8. While working with other communities the work environment was healthy 252 95.82

9. It instilled professionalism and high work values 253 96.20


1.6.8 Level of susceptibility index of technical employees working with other communities

Susceptibility index is the compatibility level of technical employees working with different communities was carried out. As

discussed in the methodology, susceptibility index was calculated by taking into account the perception of the technical

employees with respect to various attributes of working with different communities. The distribution of technical employees,

according to the level of susceptibility index is given in Table 16 Susceptibility index was classified into low and high level on

the basis of the average value of susceptibility index. Employees lie above the average value of susceptibility index

representing high level of susceptibility while the remaining representing the low level of susceptibility. Out of total 263

employees, majority i.e. 88.21 per cent belonged to high level of susceptibility, while remaining 11.79 per cent belonged to

low susceptibility level as presented in Table given below:-

Table 16: Level of susceptibility index of technical employees working with other communities

Level of Susceptibility Score Number Percent

Low <=8 31 11.79

High > 8 232 88.21

Total 263 100.00





1.6.9 Association between employees productivity and susceptibility level of technical employees-Chi square test

Chi square test was applied to test the following hypotheses:

Null hypothesis (H0): There is no significant association between employees productivity and susceptibility level technical

employees of the organization.

Alternative hypothesis (H1): There is significant association between employees and susceptibility level of technical


The observed and expected frequency with respect to low and high susceptibility level of technical employees in relation to

productivity is given in Table 17. The results showed that the calculated value of chi-square (45.227) which was very high and

the p-value was less than (0.01). Therefore, the Null hypothesis stood rejected, which revealed that the level of employees

productivity of technical employees vary significantly in relation to the susceptibility level of technical employees of the

organization.

Table 17: Association between employees productivity and susceptibility level of technical employees

Susceptibility Index

Level of Productivity Low (<=8) High (>8) Total

Low (up to Rs 5603/hrs) Count 31 84 115

Expected Count 13.6 101.4 115

High (> Rs 5603/hrs) Count 0 148 148

Expected Count 17.4 130.6 148


Expected Count 31 232 263


a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 13.56.

b. Computed only for a 2x2 table

1.6.10 Association between employees efficiency and susceptibility level of technical employees-Chi square test

Chi square test was applied to test the following hypotheses:

Null hypothesis (H0): There is no significant association between employees efficiency and susceptibility level technical


Alternative hypothesis (H1): There is significant association between employees and susceptibility level of technical


The observed and expected frequency with respect to low and high susceptibility level of technical employees in relation to

productivity is given in Table 18. The results showed that the calculated value of chi-square (45.227) which was very high and

the p-value was less than (0.01), therefore the null hypothesis stood rejected, which revealed that the level of employees

efficiency of technical employees vary significantly in relation to susceptibility level of technical employees of the

organization.

Table 18: Level of Productivity and Pearson Chi-square

n n on on n

Low Count 10 13 28 11 15 77

Expected count 4 5.4 11.6 17.4 38.7 77

Medium Count 1 2 4 37 36 80

Expected count 4.1 5.6 12 18 40.2 80

High Count 0 0 0 0 56 56

Expected count 2.9 3.9 8.4 12.6 28.1 56

Total Count 11 15 32 48 107 213

Expected count 11 15 32 48 107 213

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-square 1.458 E2a 8 0

Likelihood Ratio 158.84 8 0


N of Valid Cases 213


a. 4 cells (26.7%) have expected count less than 5. The minimum expected count is 2.89.




1.6.11 Motivation level of non-technical employees in relation to cross cultural variation

The status of motivation level of non-technical employees of the organization in relation to cross cultural variations across two

period of time was tested by developing following hypotheses:-

Null hypothesis (H0): Motivation level of non-technical employees in relation to cross-cultural variation in the organization

did not vary significantly across two periods.

Alternative hypothesis (H1): Motivation level of non-technical employees in relation to cross-cultural variation in the

organization varied significantly across two periods.

The motivation level of non-technical employees of the organization in relation to cross cultural variations across two period of

time is given in Table 19. It was evident that proportion of non-technical employees reporting 'Excellent motivation' increased

from 21.62 per cent in period-I to 46.02 per cent in Period-II. The value of z-score corresponding to 'excellent motivation' and

'Average motivation' came out to be greater than that of the critical level (2.576 at 1%: 1.96 at 5%) which further indicated that

there was significant variations in the employees motivation in the case of non-technical employees across two point of time.

Rather, the level of employees motivation in relation to cross cultural variations across two period of time was improved

significantly, as the results of the data analysis were observed to significant as shown in Table 4.39.

Table 19: Distribution of non-technical employees according to motivation

Particulars Period-I (1978-79 to 1991-92) Period-II (1991-92) to 2017-18) Z-test Significance level

No motivation 2 5.41 9 5.11 0.073 Ns

Some motivations 4 10.81 9 5.11 1.316 NS

Avg. motivation 16 43.24 38 21.59 2.752 **

Good motivation 7 18.92 39 22.16 0.435 NS

Excellent motivation 8 21.62 81 46.02 2.736 **


**Significant at 5% level.

1.6.12 Level of Attitude of non-technical employees in relation to cross cultural variation

The status of attitude level of non-technical employees of the organization in relation to cross cultural variations across two

period of time was tested by developing following hypotheses:-

Null hypothesis (H0): Attitude level of non-technical employees in relation to cross-cultural variation in the organization do

not varied significantly across two periods.

Alternative hypothesis (H1): Attitude level of non-technical employees in relation to cross-cultural variation in the

organization vary significantly across two periods.

Table 20: Status of different efficiency, productivity and competitiveness measures of non-technical employees between

two point of time

Employees efficiency indicators Period-I (1978-79 to

1991-92)

Period-I (1991-92 to

2017-18)

t Sign. (2-tailed) Significance level

Sense of competition and

competitiveness

3.51 4.17 3.13 0.002 **

Employees performance 3.46 4.09 2.937 0.004 **

Time given to achieve the targets 3.62 4.04 1.897 0.059 *

Employees Handling 3.46 4.00 2.589 0.01 **

Employees Coordination 3.54 4.10 3.074 0.002 **

Communication skills 3.38 4.09 3.265 0.001 **

Motivation 3.41 3.99 2.795 0.006 **

Attitude 3.43 3.99 2.723 0.007 **

Threats 3.95 4.76 5.268 0.00 **

Employees conflicts 2.03 1.24 5.334 0.00 **

Works Environment 3.41 4.08 3.181 0.002 **

Very poor time sense 3.30 3.99 3.329 0.001 **

Training 1.35 1.65 2.652 0.009 **


Note: ** and *significant at one and five per cent level of significance




CONCLUSIONS

It can be concluded from the above analysis that all the three objectives with which the present research paper started were

fulfilled. As mentioned above various statistical techniques such as trend analysis, two proportion Z-test, chi-square test,

regression analysis, susceptibility analysis etc. techniques were used. The results clearly indicated that there was significant

improvement in the competitiveness, motivation, attitude, work culture and work environment of the employees. There were

no feeling of demotivation attitudinal problem or work conflicts and lack of sense of competitiveness among the employees of

the organization under the study.

REFERENCES

[1] Ying Pan and Binglu Zhao (2017) cross-cultural employees motivation in International Companies, in Journal of Human

Resource and Sustainability studies (05) (04) 215-222.

[2] Faradeh Salili (1996) Achievement motivation: A cross-cultural comparison of British and Chinese students, Education

psychology, 16(3), 271-279.

[3] Carl F. Fey (2005), “opening the Black Box of motivation: A cross-cultural comparison of Sweden and Russia.

[4] Michele J. Gel fand, Mariam Erez and Zeynep Aycan(2006), cross-cultural organization bahaviour in Annual Review of

Psychology, Vol. 58: 479-514, 2007, first published online as a review in advance in Oct. 17, 2006.

[5] Sagie, Abrahim, Elizur, Dev, Yamaruchi Hurotsugu (1996), The structure of strength of achievement motivation. A cross-

cultural comparison in journal of organizational behaviour, volume 17, Issue 5.

[6] Inder Science (2010), linking Academica.Business and industry through Research in

[7] European Journal of cross-cultural competence and Management, vol 1,No 2//3.

[8] Al-Jenaibi (2010) the effects of Cultural Diversity in the workplace in Journal of Diversity management, Dec2014

volume9,(Al Jenaibi2010)

[9] Mathew Jassy (2019),, influences of cultural Differences and Diversity in Journal IACCM, Inder science publishers

[10] Tagreed issa kawar, princess Sumaya 2012, Cross- cultural differences in management, in political science,Corpus

ID:56388727

[11] Aycan et al. (2000), Impact of culture on Human Resource management practices:A 10-country comparison in applied

Psychology :An International review,49(1) (2000),pp192-221.

issn : 2454-9150 vol-06, issue-08, nov 2020 cross-cultural

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