Perceived Organizational Support as Predictor of the Three Components of Organizational Commitment

Abstract

The objective of this research was to determine the effect of perceived organizational support on the three components of organizational commitment. Primary data through survey questionnaire was collected from the college teachers of Sindh Province Pakistan. Through the empirical investigation of the data it was found that college teachers perceived support from their organization and they were committed to their organization. Perceived organizational support was found to have significant effect on the affective, continuance and normative commitment of the teachers. However the effect of perceived organizational support on normative commitment was lesser than its effect on affective and continuance commitment. This study contributed to determine the effect of perceived organizational support on the commitment level of the college teachers in context of Pakistan. The implications of the results are discussed.

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PATRON-IN-CHIEF
Prof. Dr. Parveen Shah
Vice Chancellor
Shah Abdul Latif University,
Khairpur
Patron
Prof Dr Ghulam Murtaza Maitlo
Dean
Faculty of Management Sciences
Shah Abdul Latif University,
Khairpur
EDITORIAL BOARD
Prof. Dr. Ikhtiar Ali Ghumro EDITOR-IN-CHIEF
Dr. Riaz Ahmed Mangi Editor
Syed Zulfiqar Ali Shah Sub-Editor

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EDITORIAL ADVISORY BOARD
Prof. Dr Amanat A. Jalbani Member
Dr Ahmed Nawaz Hakro Member
Prof. Dr. Abdul Naveed Tariq, Member
Dr. Andrea Appolloni Member
Prof. Srinivas Inguva Member
Bozidar Radenkovic Member
Prof. Dr. Arta Musaraj Member
Murat Sakir Erogul Member
Dr. Giannakoulas Yiannis, Member
Marusya Ivanova Member
Dr. Desislava Stoilova Member
Rong Zhang Member
Svietlana Den'ga Member
Mauricio Martinelli Luperi Member
Masashi Sakamoto Member
Dr Kamran Sidiqui Member
Dr Shazia Nauman Member
Dr. Samina Khalil Member
Prof. Dr. Ashique Hussain Jhatial Member
Prof. Dr. Naimatullah Shah Member
Prof. Dr. Muhammad Aslam Memon Member
Dr. Khalid Ahmed Mangrio Member
Prof. Dr. Muhammad Saleem Rahpoto Member
Dr. Habibullah Magsi Member
Prof. Dr. Subhan Khatoon Gaad Member
Dr. Ijaz A. Qureshi Member
Dr. Muhammad Qasim Rind Member
Dr. Nadeem Malik Member
Dr. Syed Asad Raza Shah Abidi Member
Prof. Dr. Amir Hussain Shar Member
Prof. Dr. Nadeem Syed Member
Prof. Dr. Mumtaz Ali Junejo Member

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Notes on Editorial Board
Prof. Dr Amanat A. Jalbani Member
International Technology University,
San Jose, California. USA
Email: ajalbani@gmail.com
Dr Ahmed Nawaz Hakro Member
Kuwait
Email: nawazhakro@hotmail.com
Prof. Dr. Abdul Naveed Tariq, Member
Seneca College of Applied Arts and Technology
Toronto, Canada
Email: antariq@yahoo.com
Dr. Andrea Appolloni Member
School of Economics
University of Rome, Italy
Email: andrea.appolloni@uniroma2.it
Prof. Srinivas Inguva Member
George Brown College Toronto, Canada
Email: drsrinivas_i@yahoo.com
Bozidar Radenkovic Member
University of Belgrade, Serbia and Montenegro
Email: boza@myelab.net
Prof. Dr. Arta Musaraj Member
Academicus - International Scientific Journal, Albania
Email: arta_musaraj@hotmail.com
Murat Sakir Erogul Member
Thompson Rivers University, Canada
Email: muraterogul@gmail.com
Dr. Giannakoulas Yiannis, Member
DEREE-The American College of Greece
Email: yanyan@ote.gr
Marusya Ivanova Member
Tsenov Academy of Economics, Bulgaria
Email: marusia@uni-svishtov.bg.

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Dr. Desislava Stoilova Member
South-West University "Neofit Rilski", Bulgaria,
Email: dstoilova@abv.bg
Rong Zhang Member
Fukuoka, Waseda University, Japan
Email: zhang@nishitech.ac.jp
Svietlana Den'ga Member
Poltava university of economics and trade, Ukraine
Email: denga_s@mail.ru
Mauricio Martinelli Luperi Member
Getúlio Vargas Foundation São Paulo Area, Brazil
Email: mluperi@gmail.com
Masashi Sakamoto Member
Hokkaido University. Japan
Email: msak.london@gmail.com
Dr Kamran Sidiqui Member
University of Dammim
Saudi Arabia
Dr Shazia Nauman Member
Lahore Leads University, Pakistan
Email: shaznaum@yahoo.com
Dr. Samina Khalil Member
AERC, University of Karachi, Pakistan
Email: samina.khalil@gmail.com
Prof. Dr. Ashique Hussain Jhatial Member
University of Sindh, Jamshoro.
Email: ajhatial@hotmail.com
Prof. Dr. Naimatullah Shah Member
University of Sindh, Jamshoro.
Email: syednbshah@gmail.com
Prof. Dr. Muhammad Aslam Memon Member
Shah Abdul Latif University, Khairpur.

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Dr. Khalid Ahmed Mangrio Member
Sukkur IBA
Email: mangrio85@yahoo.com
Prof. Dr. Muhammad Saleem Rahpoto Member
Shah Abdul Latif University, Khairpur
Dr. Habibullah Magsi Member
Sindh Agriculture University.Tandojam
Email: habib_magsi2000@yahoo.com
Prof. Dr. Subhan Khatoon Gaad Member
Shah Abdul Latif University, Khairpur
Dr. Ijaz A. Qureshi Member
University of Lahore
Email: ijaza.qureshi@gmail.com
Dr. Muhammad Qasim Rind Member
NCBA & E Lahore
Email: qasim.rind@yahoo.com
Dr. Nadeem Malik Member
University of Baloachistan
Email: nadeem_malik_uob@yahoo.com
Dr. Syed Asad Raza Shah Abidi Member
Shah Abdul Latif University, Khairpur
Prof. Dr. Amir Hussain Shar Member
Shah Abdul Latif University, Khairpur.
Prof. Dr. Nadeem Syed Member
SZABIST Karachi
Email: nadeem.syed@szabist,edu,pk
Prof. Dr. Mumtaz Ali Junejo Member
Professor Department of Commerce
Shah Abdul Latif University, Khairpur.

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Notes of contributors
01- Prof. Dr. Ikhtiar Ali Ghumro
Professor Department of Commerce
Shah Abdul Latif University, Khairpur.
02- Mr. Hussain Amar Dayo
Lecturer Govt: Islamia Arts Commerce College
Sukkur.
03- Prof. Dr. Riaz Ahmed Mangi
Professor Department of Commerce
Shah Abdul Latif University, Khairpur.
04- Mr. Aneel Kumar
Assistant Professor Department of Commerce
Shah Abdul Latif University, Khairpur.
05- Prof. Dr. Hassan Jawad Soomro
Professor Department of Commerce
Shah Abdul Latif University, Khairpur.
06- Prof. Dr. Muhammad Masiullah Jatoi
Professor Department of Business Administration
Shah Abdul Latif University, Khairpur.
07- Ms. Safia Khan
MS Scholar @ Department of Business Administration
Shah Abdul Latif University, Khairpur
08- Mr. Shoaib Hyder
MS Scholar @ Department of Business Administration
Shah Abdul Latif University, Khairpur

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SALU-CER December (2015)
01-08
Purchasing Behavior of Rural Consumers Migrated To Urban
Areas: A Case Study of Sukkur and Khairpur Districts
Dr. Ikhtiar Ali Ghumro*, Hussain Amar Dayo**, Dr. Riaz Ahmed Mangi***
Abstract: - Many people migrate from rural areas to urban areas due to better infrastructure.
Purchasing Behavior of rural migrants is described and influenced by five study variables which
include Brand Switchover Behavior (BSB), Purchasing Consciousness (PC), Enjoy Purchasing (EP),
Income/Pocket Money (INC/PM) and Price Consciousness / Quality Consciousness (PRC/ QC). This
study is carried out as a Case Study of Sukkur and Khairpur districts in which an attempt has been
made to understand the Purchasing Behavior of rural consumers who have migrated to urban areas of
Sukkur and Khairpur districts. A close ended survey was conducted from 383 respondents and data was
analyzed by using Descriptive Statistics and Factor Analysis. Results of study suggest that rural
migrants show Brand Switchover Behavior (BSB) as they switch brands in urban market. Further study
discloses that rural migrants show Purchasing Consciousness (PC) and they Enjoy Purchasing (EP) in
urban market. Migrants also consider Income/ Pocket Money (INC/PM) on purchasing. Results also
show that rural migrants have Price Consciousness/ Quality Consciousness (PRC/QC) in urban market.
Key Words: Consumers, Behavior, Switchover, Consciousness
1.0 Introduction
Purchasing Behavior is defined as a process that people adopt while they purchase and consume
any product tangible or intangible and ideas with an ultimate object of satisfying the needs and
wants (Kotler & Keller, 2011). There is an inequality of infrastructure, education and health
facilities between cities and villages and this inequality becomes a major instinctive force for
people living in rural areas to migrate to urban areas (Devadas & Manohar, 2011). They further
added that there is sizeable number of people who are migrating from rural areas to urban areas
in search for a better future, better job opportunities along with satisfactions of personal needs.
Migration in Pakistan has increased about six times since independence (Karim & Nasar,
2009)due to better infrastructure and more facilities available.
* Professor, Department of Commerce, Shah Abdul Latif University Khairpur
** Lecturer, Govt: Islamia Arts & Commerce College Sukkur
*** Professor Department of Commerce, Shah Abdul Latif University Khairpur.

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Purchasing Behavior has remained focus of study for urban and rural consumers or their
comparison. Researchers have been working on Purchasing Behavior of urban consumers and
rural consumers. The current study is conducted with a view to comprehend the Purchasing
Behavior of migrant consumers regarding personal care products in Sukkur and Khairpur
districts.
This study would help companies attract and retain migrated consumers by understanding factors
affecting their Purchasing Behavior. By analyzing purchasing behavior a more comprehensive
view of social aspect that migrants create by their decisions regarding purchasing behavior is
identified as migrants becomes used of factors for taking purchasing behavior.
2.0 Research Problem
Rural consumers who have migrated to urban areas can constitute a good market if their
Purchasing Behavior is completely studied in urban market environment which has not yet been
(Devadas & Manohar 2011). There is a significant relation between people who migrate and
their Purchasing Behavior (Chen et al, 2003). There is no significant study on Purchasing
Behavior of rural consumers who have migrated from their native places to urban area in
Pakistan. It is necessary to comprehend the Purchasing Behavior of those consumers who are not
urban consumers by birth. Research Problem for this study is to understand and chalk out the
factors affecting Purchasing Behavior of rural consumers who migrated to urban areas of Sukkur
and Khairpur districts.
3.0 Study Objectives
This research study has following objectives.
(1) To understand the Purchasing Behavior of rural consumers who have migrated to urban
areas of Sukkur and Khairpur districts.
(2) To describe factors effecting Purchasing Behavior of rural consumers who have migrated
to urban areas of Sukkur and Khairpur districts.
4.0 Literature Review
Shih, Yu, and Tseng (2015) worked on Purchasing Behavior of consumers. They found that
Purchasing Behavior of consumer is influenced by characteristics that a product possesses. Their
study revealed that consumer Purchasing Behavior is affected and influenced by satisfaction of
consumer with reference to product. They concluded with a finding that consumer purchases a
product once consumer is satisfied with different characteristics and attributes of a product.
Joshi et al. (2012) in a study found out that rural consumers who have come to cities for study
purposes are attracted by color, pricing and shape when they show their Purchasing Behavior on
mobile phones. Their study can be considered a significant one in trying to identify different
variables which are affecting a migrant consumer while they purchase any product. Pricing plays
an important role while purchasing a product and above study concluded that migrants while
showing Purchasing Behavior in cities become more Price conscious. Zameer et al. (2012)
conducted their study on rural migrants and according to their study at the time of independence
Pakistan was a country where two - third of the population was living in rural areas but this trend

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has changed with passage of time. They further add that this change of trend has mainly occurred
because cities have developed at rapid pace and have obtained infrastructural superiority.
According to them cities and urban areas have more to offer in the field of employment,
education and awareness forcing people to migrate. Devadas and Manohar (2011) worked on
purchasing patterns and behavior that are shown by rural consumers who have migrated to
urbanized environment in India According to them migrated consumers show Brand Switchover
Behavior as they switch the brands in urban environment. Hamid (2010) found that there is an
increase in rural to urban migration in Pakistan. Amanor-Boadu (2009) argued that rural migrant
consumers focus on attractiveness of shops along with its location which creates consciousness
to purchase in them. Sun and Wu (2004) conducted a study on urban and rural consumers. The
objective of the study was to find out if there exists any similarity of Purchasing Behavior
between urban and rural consumers. This study was conducted in China. They found out that
there is no similarity in the behavior of urban and rural consumers as far as marketing mix is
concerned and both consumers behave differently while they purchase the product. They further
added that consumers focused on price and quality as they were worried about the price of
products when they made their purchases and their qualitative structure. Lau-Gesk (2003)
worked on consumer Purchasing Behavior and their research concluded that migrant consumer
must involve income while showing Purchasing Behavior. He also worked on income with
relevance to rural migrants and is of the opinion that migrants earn more income after migration
and then they consider income or any other source available before purchasing at urban
environment.
5.0 Study Model
Figure: 01
The study model for this study has been adopted and modified considering the ―American
consumer satisfaction index model (2009)‖ developed in University of Michigan’s Ross School
of Business. This model is suggesting that Purchasing Behavior of migrants is affected by Brand
Switchover Behavior, Purchasing Consciousness, Enjoy Purchasing, Income/ Pocket Money and
Price Consciousness/ Quality Consciousness.

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6.1 Methodology
Quantitative methodology has been used in this study to comprehend Purchasing Behavior of
migrants in Sukkur and Khairpur districts. Population for the study contains Rural migrants who
have spent three to ten years time in urban areas of Sukkur and Khairpur districts and estimated
population is 100000.Migrant Students who earn Income or receive Pocket Money from colleges
(age ranges from 16 to above 20 years) of Sukkur and Khairpur districts have been taken as
Sample and Convenient Sampling technique has been used. Sample size for the study is 383
determined on the basis of table given by (Saunders et al., 2009) and derived on formula given
by (Krejcie& Morgan, 1970). Adopted and modified questionnaire of (Devadas & Manohar,
2011) has been used to get responses.
6.2 Analysis and Results
Data has been analyzed using SPSS software.
6.3 Factor Analysis
Factor Analysis has been used to understand factors effecting Purchasing Behavior of rural
migrants in Sukkur and Khairpur districts.
(a) Extraction of Factors
Figure: 02
Based on Eigen Values five factors were retained for further observation which explain
Purchasing Behavior by 62.149%.
(b) Rotated Component Matrix using Varimax Rotation

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Table: 01: Rotated Component Matrix
Strong loadings on all items suggest that Purchasing Behavior of rural migrants is strongly
affected by above five factors and items of these factors.
7.0 Study Hypotheses and their Acceptation/ Rejection
H:1: Rural consumers who have migrated to urban areas of Sukkur and Khairpur districts show
Brand Switchover Behavior (BSB) by switching brands in urban market:
Figure: 03
Result of Descriptive Analysis show that Rural Migrants have Brand Switchover Behavior
(BSB) with mean value of 3.56 suggesting that migrants have agreed that they show Brand

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Switchover Behavior by switching brands in urban market. Further 61% of migrants have agreed
that they show Brand Switchover Behavior by switching brands in urban market.
H:2: Rural consumers who have migrated to urban areas of Sukkur and Khairpur districts show
Purchasing Consciousness (PC) while purchasing in urban market:
Figure: 04
Result of Descriptive Analysis show that Rural Migrants show Purchasing Consciousness (PC)
with mean value of 3.61 suggesting that migrants have agreed that they show Purchasing
Consciousness in urban market. Further 66% of migrants have agreed that they show Purchasing
Consciousness in urban market.
H:3: Rural consumers who have migrated to urban areas of Sukkur and Khairpur districts
Enjoy Purchasing (EP) while purchasing in urban market:
Figure: 05
Result of Descriptive Analysis show that Rural Migrants Enjoy Purchasing (EP) with mean value
of 3.62 suggesting that migrants have agreed that they Enjoy Purchasing in urban market. Further
57% of migrants have agreed that they Enjoy Purchasing in urban market.
H:4: Rural consumers who have migrated to urban areas of Sukkur and Khairpur districts
consider Income/pocket money (INC/PM) while purchasing in urban market:

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Figure: 06
Result of Descriptive Analysis show that Rural Migrants have Income/Pocket Money (INC/PM)
with mean value of 3.88 suggesting that migrants have agreed that they consider Income/Pocket
Money before Purchasing in urban market. Further 79% of migrants have agreed that they
consider Income/Pocket Money in urban market.
H:5: Rural consumers who have migrated to urban areas of Sukkur and Khairpur districts show
Price/Quality Consciousness (PRC/QC) while purchasing in urban market:
Figure: 07
Result of Descriptive Analysis show that Rural Migrants have Price Consciousness/Quality
Consciousness (PRC/QC) with mean value of 3.50 suggesting that migrants have agreed that
they purchase products of low price and good quality. Further 64.3% of migrants have agreed
they purchase products of low price and good quality.
8.0 Conclusion
This study was intended to understand a very interesting aspect relating to purchasing behavior
of rural consumers who have migrated to urban areas of Sukkur and Khairpur districts. Results of
the study have shown that Purchasing Behavior of rural consumers who have migrated to urban
areas of Sukkur and Khairpur districts is affected by Brand Switchover Behavior (BSB),
Purchasing Consciousness (PC), Enjoy Purchasing (EP), Income/Pocket Money (INC/PM) and
Price Consciousness/Quality Consciousness (PRC/QC). This generally creates attraction for
companies and organizations to focus on these factors and design suitable strategies to target
these factors which affect Purchasing Behavior of rural consumers who have migrated to urban
areas of Sukkur and Khairpur districts and achieve desirable results

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References
Amanor-Boadu, V. (2009). In search of a theory of shopping value: The case of rural
consumers. Review of Agricultural Economics, 31(3), 589–603.
Chen, Z., Lu, M., & Pan, H. (2003). The effects of migration on interregional
differentials in consumer behavior: Evidence from the baise district, Guangxi, China. Paper
Presented at the UNU/WIDER Project Conference on spatial inequality in Asia, United
Nations University Centre, Tokyo.
Devadas, A., & Manohar, H. L. (2011). Shopping behavior of rural consumer migrated
to urban area in the Indian context - An emerging market. African Journal of
Business Management, 5(6), 2276–2282.
Hamid, S. (2010). Rural to urban migration in pakistan: The gender perspective (No.
56). PIDE Working Papers.
Joshi, B. H., Mehta, A. B., Patel, B. A., & Patel, K. (2012). Usages of Mobile Phone by
rural consumers: with special reference to collegian students of Palanpur taluka.
International Journal of Multi-discliplinary and Academic Research, 1(2), 1–16.
Karim, M., & Nasar, A. (2003). Migration patterns and differentials in Pakistan: Based
on the analysis of 1998 census data, in population of Pakistan: An analysis of
1998. Population and Housing Census.
Kotler, & Keller. (2011). Marketing Management (14th ed.). London: Pearson
Education.
Lau-Gesk, L. G. (2003). Activating culture through persuasion appeals: An
examination of the bicultural consumer. Journal of Consumer Psychology,13(3), 301 to
315.
Shih, S. P., Yu, S., & Tseng, H. C. (2015). The Study of consumers’ buying behavior
and consumer satisfaction in beverages industry in Tainan, Taiwan. Journal of
Economics, Business and Management, 3(3), 391–394.
Sun, & Wu, G. (2004). Consumption patterns of Chinese urban and rural consumers.
Journal of Consumer Marketing,21(4), 245–253.
Zameer, H., Saeed, R., & Abass, R. (2012). Mobile phone buying behavior of
consumers: A comparative study of rural and urban consumers in Pakistan. Global Journal
of Management And Business Research 12(6), 54–59.

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SALU-CER December (2015)
09-19
Perceived Organizational Support as Predictor of the Three
Components of Organizational Commitment
Aneel Kumar*, Dr. Ikhtiar Ali Ghumro**, Dr. Hassan Jawad Soomro***
Abstract: - The objective of this research was to determine the effect of perceived organizational support
on the three components of organizational commitment. Primary data through survey questionnaire was
collected from the college teachers of Sindh Province Pakistan. Through the empirical investigation of the
data it was found that college teachers perceived support from their organization and they were committed
to their organization. Perceived organizational support was found to have significant effect on the
affective, continuance and normative commitment of the teachers. However the effect of perceived
organizational support on normative commitment was lesser than its effect on affective and continuance
commitment. This study contributed to determine the effect of perceived organizational support on the
commitment level of the college teachers in context of Pakistan. The implications of the results are
discussed.
Key Words: Perceived Organizational support, Affective Commitment, Continuance Commitment, Normative
Commitment
1.0 Introduction
Every organization wants the employees who are knowledgeable, experienced, skilful,
supporting and so on. But this is the world of give & take. It’s a reciprocal process. If an
organization has made itself ready for supporting the talent of their employees, willing to support
them to meet their current as well as future needs and valuing the efforts of their employees then
it is likely that employee would perceive organizational support which in turn would create the
organizational commitment of the employees. A great organization do needs the same support on
part of their employees but that is only possible when employees are committed to do so.
Relationship between the perceived organizational support and organizational commitment has
been studied by many researchers and they have found the significant effect of perceived
organizational support on various components of organisational commitment. Particularly
positive and significant relationship is found between perceived organizational support and
affective components of organizational commitment. In context of Pakistan a little attention has
been given to this issue. This research has taken an initiative to determine the existence of
perceived organizational support and three components of organizational commitment in the
teachers of the colleges of the two districts namely: Sukkur and Khairpur Mir’s, of the Sindh
province of Pakistan.

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* Assistant Professor, Department of Commerce, Shah Abdul Latif University, Khairpur.
** Professor Department of Commerce, Shah Abdul Latif University, Khairpur
***Professor Department of Commerce, Shah Abdul Latif University, Khairpur
2.0 Literature Review
2.1 Theoretical Background
2.1.1 Perceived organizational support
In general sense support is described as the encouragement, backing, help or assistance. Even in
day to day routine activities we need support to do work effectively and efficiently. When it
comes to organizations, it becomes very crucial for employees working in any organization to
get the support on part of their organizations. If employees feel that there is an organization that
cares about them, about their work and there is a value for their work in the organization then it
is likely that it will create a perception of organizational support in the minds of employees.
Realising the importance of perceived organizational support many organizations, researchers
started to work on the employee’s perception of perceived organizational support. In the early
study on perceived organizational support, conducted by Eisenberger, Huntington, Hutchison,
and Sowa (1986), perceived organizational support is described as, ―Employees in an
organization form global beliefs concerning the extent to which the organization values their
contributions and cares about their well-being‖. Levison H. (1965) describes that there is a
process of reciprocation between an employee and orgnizaiton. There are mutual expectations
between orgnization and an employee. When this process of mutual expections is working well
then an employee percieves psychologically support on part of the organization and which
improves ograizational functioning. Thus perceived organizational support is the pre-requisite
for creating any psychological state in the mind of employees. Once an employee perceive
organizationa support then it is likely that it will lead towards the creation of various outcomes.
One of the storongest ouctomce created by perceived organizational support is organizational
commitment.
2.1.2 Organizational Commitment
Due to its broader sense lot of definitions has been given for organizational commitment.
Bateman and Strasser(1984) defines organizational commitment as ―multidimensional in nature,
involving an employee’s loyalty to the organization, willingness to exert effort on behalf of the
organization, degree of goal and value congruency with the organization, and desire to maintain
membership‖ (p.95). Dictionary of business and management defines organizatinal commitmnet
as, ―An individual's psychological attachment to an organization and desire to remain part of it‖.
Initially Meyer & Allen (1984) suggested two dimensions of organizational commitment:
Affective and continuance commitment. Later Allen & Meyer (1990) suggested a third
dimension: normative commitment. They describe these dimensions as:
2.1.3 Affective Commitment
Affective commitment is literally being part of organizational commitment. Affectibe
commitment is described as ―Employee’s emotional attachement to, identification with, and
involovemnt in the organization‖.

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2.1.4 Continuaance Commitment
―The extent to which employees feel committed to their organization by viutue of the costs that
they feel are associated with leaving‖.
2.1.5 Normative commitment
―Employee’s feeling of perceived obligation to remain in the organization‖.
3.0 Empirical Evidence on relationship between perceived organizational
Support and Organizational Commitment and Hypotheses
Yuanquing He, Kin Keung Lai, Yagang Lu (2011) studied the effect of organizational support on
employee’s commitment in hotel industry of China. They found that among various dimensions
of organizational support namely managerial support has the greatest influence of employee’s
commitment. Secondly co-worker relationship had positive influence on affective commitment.
Role ambiguity could not be proved as predictor of affective commitment.
Nasrin Arshadia (2011) found that in employees of an industrial organization of Iran, perceived
organizational support was positively related to organizational commitment and negatively
related to turnover intention.
Lynn McFarlane Shore and Sandy J. Wayne (1993) found positive and significant relationship
between perceived organizational support and AC; however they found negative insignificant
relationship between perceived organizational support and continuance commitment.
Rhoades, L., & Eisenberger, R. (2002) conducted the Meta analysis of 70 studies of different
researchers and found that perceived organizational support has strong and positive effect on AC
while perceived organizational support was found to have a small negative relationship with
continuance commitment. Moreover it was found that perceived organizational support has a
significant effect on turnover intention of the employees.
Meyer et. al. (2002) also conducted the Meta analysis of 155 studies. Their focus was to
determine the antecedents, correlates and consequences of various dimensions of organizational
commitment. Their findings related to this research were that, correlations between the three
dimensions of commitment namely, affective, normative, continuance, were negative. Among
these three dimensions, affective commitment had strong negative relationship with turnover
cognition followed by normative and continuance commitment.
Linda et al. (2001) found that for two year sample data, perceived organizational support was
positively related to temporal change in AC but AC was not associated with temporal change in
perceived organizational support. Similar results were found for three year sample data. Thus in
this study it was proved that perceived organizational support leads toward AC
Tek -Yew Lew (2009) found that in contrary to many studies perceived organizational support
does not have a significant direct effect on turnover of the employees but perceived
organizational support does have a direct significant effect on AC of the employees. However
AC also significantly reduces turnover intention of employees. Thus findings of their research

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suggest that employee who were higher on perceived organizational support, showed stronger
AC and in turn they were less likely to leave the organization.
Godfrey Tumwesigye (2010) and Darolia et al. (2010) found that perceived organizational
support is positively and significantly related to all three components of organizational
commitment.
Makanjee et al. (2006) determined the relationship between the antecedents of perceived
organizational support and three components of organizational commitment. They found positive
and significant relationship between antecedents of perceived organizational support and three
components of organizational commitment.
Overall majority of the researchers have found positive and significant relationship between the
perceived organizational support and affective organizational commitment but in case of
relationship between perceived organizational support and continuance commitment some
researchers have found no relationship and negative relationship between perceived
organizational support and continuance commitment while some researchers have also found
positive and significant relationship between perceived organizational support and continuance
commitment. Thus above literature review provides us basis to hypothesize positive and
significant relationship between perceived organizational support and affective commitment
while due to mixed results for perceived organizational support and continuance commitment it
is hypothesized that there will be significant relationship between perceived organizational
support and continuance commitment but the direction of relationship is left to the results of this
research. Relationship between perceived organizational support and normative commitment has
been studied by a few and they have found significant and positive relationship between
perceived organizational support and normative commitment. Due to little research on
relationship between perceived organizational support and normative commitment it is
hypothesized that there will be significant relationship between perceived organizational support
and normative commitment but the direction of relationship is again left to the results of this
research.
Hypothesis 1: Perceived organizational support has a positive effect on affective organizational
commitment
Hypothesis 2: Perceived organizational support has a significant effect on continuance
Organizational Commitment
Hypothesis 3: Perceived organizational support has a significant effect on normative
organizational Commitment
4.0 Research Design
4.1 Sample
The Data was collected from the college teachers of two districts of Sindh province of Pakistan.
The data was collected from only the male teachers because researcher could not get access to
female teachers of the colleges. Originally around 260 questionnaires were distributed and 203
properly filled questionnaires returned by the respondents, which makes a healthy response rate
of around 78 percent.
4.1.2 Measures
4.1.2.1 Perceived organizational support

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Perceived organizational support is measured by a seven point liker scale, 08 item survey
questionnaire originally developed by Robert Eisenberger, Jim Cummings, Stephen Armeli, and
Patrick Lynch (1997). This instrument is most commonly used by many researchers for
measuring the perceived organizational support.
4.1.2.2 Organizational Commitment
Three components of Organizational Commitment namely, affective, continuance, and normative
commitment are measured by a seven point likert scale, 06 item questionnaire for each
component of organizational commitment, originally developed by Meyer, J. P., Allen, N. J., &
Smith, C. A. (1993). This instrument is also most commonly used by many researchers for
measuring the organizational commitment.
4.1.2.3 Analysis Techniques used in the Research
The unit of analysis in this research is an individual. Firstly preliminary data screening tests,
normality tests are performed and scale’s reliability is also checked. The data is analysed in two
stages. Firstly the descriptive statistical techniques such as Arithmetic mean, Standard Deviation
is determined. To check the strength of linear association between the independent variable and
dependant variable, Correlation among all the variables are determined. In the second stage
multiple regressions are run to determine the effect of perceived organizational support on three
components of organizational commitment.
5.0 Results
5.1 Demographics Analysis
The demographic analysis results for gender showed that all the respondents were male. The age
group analysis results showed that 29 percent of the respondents were between the age group of
20 to 29 years, 45 percent of the respondents were between age group of 30 to 39 years, 17
percent were between age group of 40 to 49 years and 09 percent were between age group of 50
and above. The education level analysis showed that 92 percent of the respondents had the 16
years of education, and 08 percent had 18 years (MS/M.Phil) of education. The job title analysis
results showed that around 58 percent of the teachers were lecturers, around 36percent were
assistant professors, and around 06 percent were associate professors.
5.2 Descriptive Analysis, Normality Tests, Reliability of Scales, and Common
Method Variance
Preliminary data screening tests showed no missing value or aberrant values. For checking the
normality of the data, the descriptive analysis results showed the skewness and kurtosis above
the range of normality for many items. The result of Kolmogorov-Smirnov Statistic was also
significant which suggests the abnormality of the data but this is common in primary data and
this risk is avoided with a reasonably large sample of data usually 200+ (Tabachnick & Fidell
1996, p. 73). This research has a sample of above 200 so it would not affect the analysis process.
Moreover the shapes of normality graphs (Histogram, Q-O plots and box plots) suggesting that
the data is reasonably normal. Few outliers were also detected in the normality analyses which
were adjusted to mean values before analysis. In order to handle the issue of common method
variance, Harman’s single factor test procedure was adopted. According to Harman’s single
factor test, common method variance issue can be identified through exploratory factor analysis.

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If there is common method variance in the data then a single factor should emerge in the EFA or
one factor should account for the maximum amount of variance (Podsakoff et al., 2003). In order
to check the common method variance EFA of all the item was conducted and one factor
solution accounted for less than 28 percent of the variance.
Descriptive analysis results showed that perceived organizational support has a mean of 5.211,
Affective commitment has mean of 5.321, continuance commitment has mean of 4.769, and
normative commitment showed mean result of 5.270. The reliability of scales adopted in this
study was determined through Cronbach’s Alpha. The reliability analysis results showed that
perceived organizational support scale has a reliability of .820, affective commitment scale has
reliability of .681, continuance commitment scale has reliability of .781, and normative
commitment scale has a reliability of .754. These results are given in table 01.
5.3 Correlational Analysis
Correlation between perceived organizational support and affective commitment was .588,
between perceived organizational support and continuance commitment was .581, and between
perceived organizational support and normative commitment it was .481. The correlation results
are given in table 02.
5.4 Regression Analysis
5.4.1 Perceived Organizational Support and Affective Commitment
Regression analysis results showed that perceived organizational support has a significant effect
on the affective commitment of the college teachers. Perceived organizational support explained
34 percent of variance in affective commitment. The beta coefficient result showed that one unit
change in perceived organizational support results in .61 units change in affective commitment
of the college teachers. These results are given in table 03.
5.4.2 Perceived Organizational Support and Continuance Commitment
These results showed that perceived organizational support has a significant effect on the
continuance commitment of the college teachers. Perceived organizational support explained
around 33 percent of variance in continuance commitment. The beta coefficient result showed
that one unit change in perceived organizational support results in .65 units change in
continuance commitment of the college teachers. These results are given in table 04.
5.4.3 Perceived Organizational Support and Normative Commitment
These results showed that perceived organizational support also has a significant effect on the
normative commitment of the college teachers. Perceived organizational support explained
around 18 percent of variance in normative commitment. The beta coefficient result showed that
one unit change in perceived organizational support results in .486 units change in normative
commitment of the college teachers. These results are given in table 05.
5.5 Discussion

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The preliminary data screening analysis showed no existence of the missing or aberrant values
because researcher checked all the questionnaires at the time of collecting from respondents and
requested the respondents to refill the missing/ aberrant items properly.
Cronbach’s alpha values showed the reliability of the measurement scales well above the
acceptable level. The descriptive analysis mean values showed that the teachers of colleges
agreed to perceive the support from the organization and mean results also showed the existence
of all the three components of organizational commitment. However the mean value of affective
commitment was higher than continuance and normative commitment which is consistent with
the previous research. The correlational analysis showed the positive and significant relationship
between perceived organizational support and all three components of organizational
commitment. However the relationship between perceived organizational support and affective
commitment was a little more than relationship between perceived organizational support and
continuance commitment. Relationship between perceived organizational support and normative
commitment was less than the two other components. The regression analysis results also
showed the significant effect of perceived organizational support on all three components of
organizational commitment but the effect of perceived organizational support on normative
commitment was less than the affective and continuance commitment. Thus correlation and
regressions results supported our all three hypotheses of the positive and significant relationship
between the perceived organizational support and all three components of organizational
commitment.
Overall through this study it was determined that the college teachers of the Sindh province of
Pakistan perceived the support from their organization and this support increases their
commitment to the work significantly. At college education level teachers are receiving
handsome amount of salary packages, more than sufficient number of official holidays, teachers
can work part time in other institutions as well, and Education department assigns supervisors
(Principals of colleges) within from the teachers. The workload on teachers is also adequate and
teachers do enjoy task autonomy. Due to all these factors college level teachers have perceived a
sufficient amount of organizational support which in turn increases their commitment to
organization. The affective commitment results showed that teachers were found to be
emotionally attached to their organization and they proudly identify themselves as part of college
education. Teacher’s continuance commitment level was also significant because in a country
like Pakistan where there is huge unemployment if any person is getting a job like teacher, he or
she thinks about it as a plum opportunity of their life. More over significant normative
commitment results also showed that teachers ethically think that they should be committed to an
organization where they perceive a sufficient amount of organizational support. Thus concluding
this research as a useful step through which we determined the organizational support level and
commitment level of the college teachers.
6.0 Managerial Implications
Through this study we contributed by highlighting the role of varying effect of perceived
organizational support in enhancing employees’ three commitment levels (i.e., affective,
continuance, normative). The committed employees are the productive employees. This study
established that the support provided by the organization can be very helpful to induce
employees’ commitment level either affective, continuance or normative. When an organization
is supporting the talent of their employees, willing to support them to meet their current as well
as future needs and valuing the efforts of their employees then such support is likely to increase

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the emotional attachment, the obligation to remain with the organization and the felling that the
value of such support is good enough to continuously remain committed to their organization.
7.0 Limitations
This research is not free of limitations such as:
The data used in this study was cross sectional which may create the common method variance
problem.
The sample was limited to the male respondents of public sector colleges only.
This research included only one variable to predict the organizational commitment of the
teachers while many other variables such as perceived supervisory support, job satisfaction etc.,
may have significant effect on the organizational commitment of the teachers.
8.0 Recommendations /Future Directions
It is recommended that female sample of respondent and private sector colleges may also be
included in future research.
Perceived supervisory support may moderate the relationship between the perceived
organizational support and organizational commitment. So it would be useful to determine the
interactive effect of perceived organisational support and supervisory support on the
organizational commitment of the teachers.
For more generalizable results this research may be expanded to the other areas of Pakistan as
well.

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Appendix A
Table 01: Mean, Standard Deviation, and Cronbach’s Alpha Reliability
Mean St. Deviation Alpha Coefficient
Perceived Organizational Support 5.211 .749 .820
Affective commitment 5.321 .780 .681
Continuance Commitment 4.769 .846 .781
Normative Commitment 5.270 .859 .754
Table 02: Correlation Matrix
1 2 3 4
1. Perceived Organizational Support1
2. Affective commitment .588** 1
3. Continuance Commitment .581** .394** 1
4. Normative Commitment .424** .605** .293** 1
* * Correlations are significant at 0.01 levels
Table 03: Linear Regression Results for the Effect of Perceived Organizational Support on
Affective Commitment
Model Summary
R R – Square Adjusted R-Square Std. Error of the Estimate
.588 .345 .342 .633
Predictors: (Constant), Perceived Organizational Support
Coefficients
Independent Variable β (Un.Std.) Std. Error β (Std.) t p
Perceived Organizational .612 .059 .588 10.30 .00
Support
Dependent Variable: Affective Commitment
F – Value: 106.089
Significance level: ** =.00
Table 04: Linear Regression Results for the Effect of Perceived Organizational Support on
Continuance Commitment
Model Summary
R R – Square Adjusted R-Square Std. Error of the Estimate
.581 .338 .334 .690
Predictors: (Constant), Perceived Organizational Support
Coefficients
Independent Variable β (Un.Std.) Std. Error β (Std.) t p
Perceived Organizational .656 .065 .581 10.126 .00
Support
Dependent Variable: Continuance Commitment
F – Value: 102.528
Significance level: ** =.00

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Table 05: Linear Regression Results for the Effect of Perceived Organizational Support on
Normative Commitment
Model Summary
R R – Square Adjusted R-Square Std. Error of the Estimate
.424 .180 .176 .780
Predictors: (Constant), Perceived Organizational Support
Coefficients
Independent Variable β (Un.Std.) Std. Error β (Std.) t p
Perceived Organizational .486 .073 .424 6.638 .00
Support
Dependent Variable: Normative Commitment
F – Value: 44.06
Significance level: ** =.00

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SALU-CER December (2015)
20-38
Determinants of an Investment Decision (A Case of Fertilizer
Sector in Pakistan)
Dr. Muhammad Masiullah Jatoi*, Ms. Safia Khan**, Mr. Shoaib Hyder***
Abstract: - Investment in reality is a capital sacrifice that includes risks means that every
entrepreneur and stockholder wants a profitable return on their specific investment. A case study
of three leading fertilizer firms of Pakistan is considered for outcomes, namely Engro Fertilizer,
Fauji Fertilizer and Fatima Fertilizer. Four investment-based ratio relations have been intervened
and analyzed statistically for their relation and implications to determine for investment decision
with key consideration given to risk-factor, sector investigation and company individual rating
with performance in fertilizer segment even though each one’s share market is at high pressure by
external shocks. Out of four relations three were quite significant, accepted and are found highly
meaningful to investment decision, while one is insignificant and is rejected for intervention.
Finally we propose investors with investment decision to prefer Fauji at 1st, Fatima at 2nd and
Engro at 3rd as per investment risk is concerned.
Key words: Investment and Investment Decision, Entrepreneurs, Risk-factor.
1.0 Introduction
Investment in simple is to spend or set aside capital for financial gain in future. For a person, it
may include obtaining of financial resources like stocks, mutual funds, bonds and possession of
durable goods like a car or housing. Economic perspective of investment is an increase in actual
capital, increasing a nation’s technical resources or human capital (Investment, 2006).
Investment refers to purchase of an asset with hope that it will generate return or income or
appreciate in coming time (Reilly & Brown). Multidimensional consideration of financial
management has remained almost in appropriate decision making for better outcomes for its
peers; knowing about what to invest, when to invest (McDonald & Siegel, 1982), how much to
invest and where to invest is not a surprising question to ends of financing authorities and
investors; whereby structural optimization of different investment opportunities in a sector is a
social responsibility of an investor to provide sustainable state for his financial equity towards
his nation (Terol, Parra, & Fernández, 2015).
* Professor, Department of Business Administration, Shah Abdul Latif
University, Khairpur Mirs
** MS Scholar Department of Business Administration, Shah Abdul Latif
University, Khairpur Mirs
*** MS Scholar Department of Business Administration, Shah Abdul Latif University,
Khairpur Mirs
Investment process is critical (Osnabrugge, 2000) as proper screening of good opportunities,
searching for better and finally investing in best option is ultimate goal therein to ensure

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maximization of return for managing working investment by an individual or firm in stock of an
entity (Kaplan & Stromberg, 2001). It is accepted that screening for equity-decisions adds value
to investment and contracting with intermediaries minimizes risk factor (Kaplan & Stromberg,
2001). Therefore decisions for investment are major concerns in financial situations of a
corporation in every segment of an economy (Fu & Liu, 2015). Evaluating an investment
decision involves various techniques, but in this article we would be working around the circle of
firm’s financial operations, with rate of risk (Terol, Parra, & Fernández, 2015) and return
involved to measure up to what extent leading fertilizer firms have been quite successful in
achieving sector’s financial stock-related goals of wealth maximization.
It is originated that management is more conscious to provide value based outcomes for firm’s
success with a fact that investors construe for rational decision about investment (Myers &
Majluf, 1984); where profitability is a utility function in financial perspectives of investment
decision with manipulation of side-risk (Terol, Parra, & Fernández, 2015). Investment decisions
are highly intrinsic (Myers & Majluf, 1984); its dimensions are changing from reward
enhancement to utility enhancement that is risk reduction (Virlics, 2013). Simplistic and discrete
structures are intervened to confirm estimation of numerical of firms in fertilizer segment; so that
proper outcomes could be submitted to concerned parties for an investment decision. The study
highlights complete case study of each firm with its overall portfolio performance (Terol, Parra,
& Fernández, 2015). The issuance of common stock with a significant operational strategy
(Myers & Majluf, 1984) and monetary policy are significant influential tool to corporate
investment in a specific sector that helps to adjust fluctuating situation in different required times
for leverage of sector resources (Fu & Liu, 2015). An agency function can also of course be an
interest-option for funds utilization by investment source (Kaplan & Stromberg, 2001).
2.0 Theoretical Background For Investment Decision
Investment decisions are likely to be done on the basis of accessibility and affordability of
opportunities and optimization of resources and their proportion of contribution to profitability of
investment (Wanjun, Ting, Ning, Qiji, & Bin, 2013). Investment evaluation criteria depend
heavily on characteristics of entrepreneurs, financial scenario and marketing perspectives of
industry (Monika & Sharma, 2015). One research instructs that investment appraisals may be
prepared for working decisions in which it must be defined by nature of investment that either it
is financial or economic to best prescribe its commonalities of operations and differences of
performance found in different firm’s stock in capital market (Witt, Lill, & Nuuter, 2015). A
conceptual view-point of investment decision is when a disposed product is taken as a raw
material, processed as a modified one and offered to market as a new one, less in price and high
in profit percentage requires careful concern (Kafuku, Saman, Yusof, Sharif, & Zakuan, 2015).
The corporate behavior of financing can explain tendency to depend on internal-funds financing
or may prefer debt for equity by external resources for investment decision (Myers & Majluf,
1984). Making structured contracts, pre-investment selection and after-investment monitoring
and evaluation are highly interrelated to provide successful returns for investor (Kaplan &
Stromberg, 2001) confirming that investing funds in sustainable portfolio is a social
responsibility of an investor (Terol, Parra, & Fernández, 2015).
Moreover, the large players are having a competitive edge of having access to extensive funds
and small-size firms face a restriction to credit limit for enhancement of operations and product

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portfolio (Mendes, Serrasqueiro, & Nunes, 2014). The focus on options of venture capital
investment provides a good measure for outcomes in a sense that decision making for investment
criteria involves a five step follow-up model; initiating from deal origination, screening,
evaluation, structure and post investment activity (Monika & Sharma, 2015). Empirics also
proves that focusing on how much an economic activity is innovative that triggers investment
dimensions and leads to economic development (Plotnikova, Korneva, & Ustuizhanina, 2015).
To know about investment determinants of old and new participating firms in industry, we must
empirically highlight and prove the variables flow for growth and return in sales, free cash flows,
size of firm, macroeconomic situations and growth level (Mendes, Serrasqueiro, & Nunes,
2014).
Investment-value depend best on determination of investment management of specific firm in an
industry, whereby industry might be in recession but the company at individual may not and is
having edge of reaping profits (Li, Yang, & Xiao, 2014). In understanding key issues related to
investment decision in different companies in distress situation with some empirical results and
validations suggests that investment behavior of firms having fewer investment options present
larger tendency to under-invest that is high risk (Gutiérrez, Azofra, & Olmo, 2014). The most
contributing risk derivatives affirms that investment decisions are subjective (one sided) in
nature but factors affecting decision are highly objective (multi-sided) as there exists an intense
portfolio of environmental forces (Virlics, 2013). If investment strategy adaptation involves
efficiency, human acceptance, scientific and technological security, infrastructural and
institutional consideration then it will surely contribute to successful creation of economic
activity and will trigger the good social system for the inhabitants (Plotnikova, Korneva, &
Ustuizhanina, 2015).
Investment related assumptions must also be supported by empirical evaluation of investment
variables (Myers & Majluf, 1984). The variables of investment may be industrial capital, human
capital, institutional potential, economic risks, financial potential, environmental risks, and
retrospective investment motion and investment inflows (Kharlamova, 2014). Further, return rate
percentage, return on investment, net present value, period of investment payback are the good
determinants to useful investment set of values (Kafuku, Saman, Yusof, Sharif, & Zakuan,
2015). It is also found that investment is determined by performance of firm, time efficiency of
return, investment size and locality, product and industry analysis (Monika & Sharma, 2015). It
is endorsed that determining additional directions to be considered when making an investment
decision is a key instrument for its success validation (Witt, Lill, & Nuuter, 2015); like changing
dimensions of time, growing needs of seeking information, higher processing time for return
would severely affect investment decisions that are completely enrolled to quality and quantity
of return or gain on investment and level of risk factor involved (Kafuku, Saman, Yusof, Sharif,
& Zakuan, 2015).
The concerns of investment security is resultant to economic security, which preserves capital fly
from economic system (Kharlamova, 2014); thereby corroborating that investment assessment
involve value-based measurement parameters like cost v/s benefit analysis, discounted cash
flows sequence (Fu & Liu, 2015), calculation of input and output factors, risk and uncertainty
figures and time being involved in operational cycle (Witt, Lill, & Nuuter, 2015). An enrichment
to assure behavioral text of corporate investment can help management to optimize overall
policies and strategies at macro level to assist increased performance (Fu & Liu, 2015). Industry-
policy also can determine structural earnings, dividend or mergers of company for strength of
profits (Li, Yang, & Xiao, 2014) as they prove this by an example of real scientific judgments of

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Chinese stock analysts and consulting firms, who makes good-best possible decisions for their
cliental system.
The value of investment opportunities homogenous in nature for industry with a complete
portfolio of investment may be formed to capture customer utility at large (Wanjun, Ting, Ning,
Qiji, & Bin, 2013); as investment decisions are based on demand push-ups (Wanjun, Ting, Ning,
Qiji, & Bin, 2013). By international facets it is highly suggested that worldwide recognized
principles, as made by IMF and World Bank else must be followed in making right investment
decision; while keeping in view the importance of past profitability index, future results and
payback time period for the investment (Virlics, 2013); where international research verifies that
monetary channel rather than credit version of investment has major irregularity in investment
setting (Fu & Liu, 2015). Firms having greater investment options poses greater propensity to
over-invest that is low risk. It at all depends on how capital investors are willing to accept and
turn weaknesses into opportunities and opportunities into extreme wealth maximization
(Gutiérrez, Azofra, & Olmo, 2014).
3.0 Research Hypothesis
a). The determinants of investment must properly be examined before
investment decision.
b). The determinants of investment are significantly contributing to investment
decision.
4.0 Manuscript Contribution
The article is a privilege addition to knowledge books of investment entities that is to hands of
creditors, investors and managers for determining value-based operations involving risk and
return of sector, keeping in view market holdings of major players. It is a thematic step to
institute key performing determinants by building financial relations; whereby we indulge
multiple research methods to construct a valid rationalization of proving to better improve
efficiency of investor decision in stock of high performing firms of fertilizer sector in overall
declining situation of country. Empirical results, sector investigation, case study of each firm,
their credit rating, SWOT analysis for investment decision deposit the study at its best in
literature contribution to its stakes. Integration of developed relations helps in prediction of
variables (Table-05). Sector study implies to policy stakes to not to restrict strategic supply of
gas resources to this sector in order to satisfy growing needs of agriculture. Case study assists
organizational management to know about leading player of industry and get their state
improved in context of better managing the same. Worldwide citation puts it an end to generate a
list of factors for best investment decisions. SWOT analysis at last is a key predictor towards
future operational vision.
5.0 Proposed Research Model
Determinants
Investment
Decision
Risk Analysis
Ratio/Return Analysis
Regression Analysis

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6.0 Research Design
Secondary data-collection method is utilized by examining annual reports of three leading
players (Engro, Fauji and Fatima) in fertilizer sector of Pakistan; rest ahead several publications
are taken into account, for citing related work of other authors to ensure study outcomes. A case
study sampling method is used to examine industry leading firms for an investment decision.
Further endorsement towards this study is given by making detailed sector investigation,
classifying company credit ratings by official authority in economy, focusing on rapid
performing last three years operations-circle of three companies, even though their share market
is at high pressures. Finally interpreting numeric of decision related variables by statistical
software PASW-18 with utilization of linear regression in order to affirm inter-relationship
between four relations formed in this study, completely tied to investment setting and decision to
provide investors with decision making information.
7.0 Sector Investigation
7.1 KSE Records
The dominancy of the three firms (Engro, Fauji & Fatima) can be observed as per their
contribution of volume (figure in millions) in fertilizers stock of KSE-100 and the same can later
be found in study for their production capacity and contribution to economic needs.
7.2 PACRA Ratings
Pakistan fertilizers industry has a capacity to produce 6.9 million metric ton of urea with 0.7
million metric ton of DAP (Diammonium Phosphate) and 2.2 million metric ton of other
fertilizers. There are bulk figures in demand curves of industry for urea consumption, where
dominancy of few players has remained a key factor of market shifting towards producer’s goals
Karachi Stock Exchange – Data Portal

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at all. Local capacity (despite of recent additions by Engro fertilizers for Asia’s second largest
fertilizer plant) trend of DAP has been failed to meet ongoing demands of agricultural houses
still and utilization of low capacity has ultimately brought a pause in gas supply to participating
firms producing the fertilizers (PACRA, 2015).
Engro holds a good PACRA rating AA- (long term) and A1+ (short term), maintaining its
portfolio with keen positive behavior in market. The same rating is assigned to Fatima Fertilizer
with comments of upgrading its portfolio that predicts stable behavior in fertilizer market
(PACRA, 2015). Fauji fertilizer company (FFC) credit quality for its group companies as per
figures of financial assets was assessed lower by reference to determination of external credit
rating; therefore internal ratings for credit circle can be determined based on their past
information to go default in meeting debts prescribed as AA- in long term) and A1+ in short term
(Forging Ahead - FFC, 2014).
8.0 Case Study
8.1 ENGRO Fertilizer
Engro Corporation, a Pakistani public MNC, Karachi based, with its subsidiaries involved in
production of fertilizers, foods, chemicals, energy and petrochemicals; with workforce strength
of 2093 employees (December, 2009), having PKR 100 billion of revenue and PKR 27 billion of
total equity. Engro has been enjoying diversified portfolio of products in its fertilizer sector and
stands in the leaders of industry. The first national branded fertilizer production house is striving
to change the tunes of farming from conventional methodologies to contemporary farming
techniques for enhancing outcomes; contributing its services since a good timeline, with a
diversified portfolio of resources in educating overall fertilizer sector of the country (Engro
Financial Report, 2014).
The Pakistan Credit Rating Agency Limited – Rating Resources

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No doubt a pioneer firm in fertilizer sector is Engro having a mark of significance for its brand
quality and price excellence as compared to imported Urea and DAP. Its new Enven plant is
highly cost efficient, providing the corporation a forging factor of progression in industry for its
profitability maximization of its shareholders in return; the corporation model heavily relies on
this business (Engro banks on fertilizer strength, 2013). Back to two years, Engro was threatened
to serious problem of lower gas supply by government side, which in turn severely affected its
production capacity to be lower down in distribution houses. But, with keen focus on the issue by
Engro management, it was resolved with an IPO offering to show the government that Engro has
a strong base in generating funds to find an alternate of gas supplier to them from private side;
later the problem was solved but yet not properly addressed by government side, but Engro is
managing its widespread resources in utilizing the same (Engro Fertilizer IPO — exquisite
timing, 2013).
8.2 Fauji Foundation Company
Fauji Fertilizer Company (FFC) being one of another major player in fertilizer sector of Pakistan,
has been contributing its services since 36 years, with production capacity of 6600 million tons
per day, involving an employee figure of 5500 individuals with its headquarters in Rawalpindi,
Pakistan. Share capital at initial level of company was amounted to 813.9 million rupees but now
share capital stands higher than Rs. 8.48 billion. In addition, FFC has more than Rs. 8.3 billion as
long term investments comprised of stakes in subsidiaries of FFCEL, FFBL, and FCCL (Fauji
Fertilizer Company Limited, 2015). FFC as per its results revelation in January 2015,
profitability figure of PKR 18,552 million was cited and Earning per share was marked with
figure of PKR 14.58, losing by 8% against results of last year as profitability accounts for PKR
20,135 million and EPS held at PKR 15.83 (Raza, 2015).
(Forging Ahead - FFC, 2014) – Annual Report

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It is witness to Pakistan’s economy, based on economic progress in 2014 with GDP sequence
fostering to 4.1% compared with 3.7% in 2013, the highest figures being achieved during last 6
years. Growth line was completely backed by manufacturing and services sectors of the
economy. Agriculture holds a key status and is considered as a source of living for rural
inhabitants, additionally providing raw materials to industrial firms; it also embarks a significant
contribution for export earnings of our nation. The sector accounts for 21% of GDP and absorbs
around 44% of country’s work force (Forging Ahead - FFC, 2014)
Study revealed that among all in Pakistan, FFC is well-known market leader. FFC is focusing on
strengthening skills of its workforce and that’s why company has best professionals in different
departments. It is efficiently utilizing gas as compared to other with acknowledged contracts by
government as well in relation to loss of gas. It is considered as highest tax payer that is main
contribution to enhancing economic growth. It also focuses on diversification; by initiating wind
energy in Pakistan, invested in Al-Hamd food for preserving fresh food and renamed it as FFF
(Fauji Fresh & Freeze), in its banking portfolio it is accredit as largest shareholder of Askari
bank that is also a positive footstep towards growth (Recorder, 2015).
8.3 Fatima Fertilizers Company Limited
Fatima Fertilizer Company Ltd, a venture firm formed by two key business houses (Fatima and
Arif Habib Group) in Pakistan was incorporated on 24 December, 2003. The company is an
integration of art production facility with production capacity in million tons of Nitric Acid,
Ammonia, Urea, Nitro Phosphate (NP), Calcium Ammonium Nitrate (CAN) and Nitrogen
Phosphorous Potassium (NPK) at city of Sadiqabad, Rahim Yar Khan (Fatima Group of
Companies, 2015). It is the biggest CAN and NP fertilizer producer in Pakistan. Because of
efficient performance Fatima is showing growth in urea production. Its main focus has remained
as ―farmer’s community education‖ and this campaign helped company to boost its sales volume.
(Fertilizers, 2014) – Annual Report

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In spite of increasing fertilizer’s prices, FF enjoys advantageous position as compare to its peers
because of its inherent advantages. Company got lion’s share in 2014 from urea whereas
continuous low cost pressure and low gas curtailment was also there but its gross margin remains
higher against its competitors. Past few years has shown stable performance for FF and this tries
to assist company to pay its debts smoothly. Continuing threats hinder FF to surpass the demand
to its operations but by its good performance demand remained stable for it (Recorder, 2014). A
deep commitment of improving lives and standards of farmers have been marked in Fatima’s
business model that ultimately plays a substantial role via increasing its productivity curves in
agriculture sector of nation for its grand contribution (Fertilizers, 2014).
9.1 Risk Analysis
Risk is an uncertainty that a spending will earn its anticipated return rate (Reilly & Brown). Risk
is different everywhere as per business geographical location; but investor at every stage tries to
minimize risk-level in investment process to generate good return (Osnabrugge, 2000).
Investment decisions are highly tied to investment risk (Virlics, 2013) and assessment of
investment is also mandatory in an economic system, where information resource is fundamental
to financing a decision for risk being involved (Kharlamova, 2014). Citing same we engage this
section explaining risk factors analyzed for leading fertilizer firms of industry. The risk has been
categorized into two factors as follows:
9.1.1 Qualitative Factors
The overall industry focuses on safety at work as its top priority, feeling its corporate social
responsibility by avoiding risk of being publically failed industry. Values of Health, Safety and
Environment (HSE) function of industry have ensured top line processes and systems for good
compliance; total recordable incident rate and safe working hours has been major contributing
instruments in measuring overall performance of division in economic industry. The ISO
certifications provide answers to those minds that are quality oriented; while process safety
management (PSM) has been a key concern to stockholders and stakes of industry for its risk
measurement. Thus, it can be concluded in a simple risk equation function as:
Qualitative Risk Factors = f (corporate risk, safety risk, quality risk & geographic risk).
9.1.2 Quantitative Analysis
Table-01
Risk Analysis (Standard Deviation & Variance)
Minimum
Maximum
Mean
Std. Deviation
Variance
Profit (After Tax) - Bn
-2935000
20860000
1.04E+07
7.88E+06
6.21E+13
Return on Capital
9.13
70.38
33.2489
26.3242
692.963
Earnings Per Share
-2.59
16.4
7.31
6.62214
43.853
Return on Equity
-17.05
80.96
37.7789
32.75457
1072.862
Sample: Engro Fertilizers; FFC; Fatima Fertilizers; (3 years data analysis)

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The industry has tremendous performance dimensions, whereby standard deviation and variance
(a relative measure to risk) for some investment ratios shows quite random effect on rate of
return (mean) of each ratio (Table-01); showing a positive relation insists that there exists a
significant relation in between taking risk and maximizing return as per economic conditions and
number of firms present in industry, while ROE and CD shows high variance. FFC and Fatima
are in profit since 2012 but Engro bears a loss in 2012 and 2013; highly suppressed of the
conditions it all turned back to astonishing results in 2014 for Engro Fertilizers. Thus, it can be
concluded in a simple risk equation function as:
Quantitative Risk Factors = f (financial risk, credit risk, earning risk & investment risk).
9.2 Developing Investment-Based Ratio Relations
The study has determined four ratios that are highly found significant for their result’s
consideration in investment decisions in different studies. The relations with basic brief
definition of each variable are depicted in Table-02. Developed four relations persist in whole
analysis, with combined numeric of three leading firms contributed in industry with regression to
better comprehend in support of formulation of hypotheses.

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Operations Circle of Industry for 2012 - 2014
The operations circle of industry shows an adornment growing relation to yearly timeline of its
business. A good judgment can be made for differentiation and comparison of three leading
firms in sector for their investment-based ratios, so that an investment decision can be made for
the stock investment in this sector in a specific company or as a whole (Table-03)
10.0 Results
Table-02
Ratio Relations Developed
No.
Independent Variable
v/s
Dependent Variable
1
Earnings per share (EPS)
v/s
Share Price (SP)
*Earnings per share: It is a gain per share, obtained when net-income is divided by number of shares
outstanding and serves as profitability of company.
*Share Price: It is a market worth (price) of a share of a company.
2
Return on Capital (ROC)
v/s
Market Capitalization (MC)
**Return on Capital: It is pay-back on capital employed, obtained when after-tax working income is divided by book
value of equity and debt capital less cash or equivalents. It is used as a ratio in financing and estimation.
*Market Capitalization: It is entire value of stock that is outstanding, calculated by multiplying per share
market-price and number of shares-outstanding.
3
Return on Equity (ROE)
v/s
Cash Dividend (CD)
*Return on Equity: It is ratio of net income of a firm to equity of an owner
***Cash Dividend: It is money directly paid to shareholders periodically, if available
4
Profit After – Tax (PAT)
v/s
Revenue/Sales (R/S)
*Profit After - Tax: It is obtained by deducting financing expenses and taxes from operating profit.
*Revenue/Sales: It is the sum of goods or services that are sold for the cost paid by clients.
Sources: *(Drake & Fabozzi, 2010); ** (Poterba, 1998); *** (Complete Guide To Corporate Finance, 2016);
Table-03
Comparative Highlights of Fertilizer Sector (2012 - 2014)
Determinants
ENGRO Fertilizer
FFC
Fatima Fertilizer
2012
2013
2014
2012
2013
2014
2012
2013
2014
Revenue/Sales (Million)
30627
50128.94
61425
74322.61
74480.61
81240
29518.62
33495.89
36169.19
Profit After-Tax (Million)
(2935)
5497.10
8207.96
20860.12
20134.55
18170.76
6111.12
8022.18
9257.8
Production Capacity (Metric Ton)
1819
1819
1819
2403
2403
2403
1181
1181
1181
Earnings Per Share (Rs.)
(2.59)
4.50
6.23
16.40
15.83
14.28
2.91
3.82
4.41
Cash Dividend (%)
Nil^
Nil^
30
155.00
153.50
136.50
20.00
25.00
27.50
Share Price (Rs.)
49.41”
47.21”
86.96”
148.35
110.80
116.22
24.59
25.25
30.76
Return on Capital (%)
9.13
22.04
22.81
70.38
68.41
64.50
10.38
14.48
17.11
Return on Equity (%)
(17.05)*
26.90
27.57
80.96
80.05
70.79
21.11
24.49
25.19
Market Capitalization (Million)
N/A”
64**
103**
188736.51
140963.97
148992
51639
53025
64596
Sources: Company Annual Report(s) – 2014 & KSE Company Report(s) - 2014
* refers to Loss; ** refers to Billion; ^ refers to source EFL Final Prospectus 2013(P#66); ” refers to source (SCS-KSE Karachi Stock Exchange Brokerage, 2015)

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The results through statistical software have been shown in Table-04 and Table-05 for better
illustration of model fitness, relations and significance in between independent and dependent
variables (determinants) selected for investment decision.
10.1 Earnings per Share v/s Share Price
The Adjusted R Square shows that how much data is fit for defined relation; while the rest is
considered as error term. The relation between two variables is analyzed and value of adjusted R
Square is about 0.715 or 71.5% (Table-04) that indicates strength of relation for independent
variable (EPS) to dependent variable (SP); whereas 28.5% is error term which shows that just
EPS is not overall determinant of SP in investment market. It shows that this relation is
significant at p<0.001 and meaningful to its formation in investment perspectives.
Table-05 indicates the correlation values for these two variables towards others, with a highest of
significance towards all except MC. Covariance in Table-04 shows dependency of two variables;
the dependent variable (SP) is positive and suggests that two variables covariates (moves with
similar difference and space as per their value increase and decrease) in investment market. The
beta value suggests for existence of direct relationship in between two that is 0.866 or 86.6% to
show a consistent contribution of EPS in formation of new value determination for SP in equity
investment house.
10.2 Return on Capital v/s Market Capitalization
The relation reveals value of adjusted R Square for about -0.055 or -5.5% (Table-04) that
indicates weakness of relation for independent variable (ROC) to dependent variable (MC);
whereas 105% is held for error term, which shows mostly the ROC is not a determinant of MC in
investment market. It is not significant as p>0.005 providing meaning in a sense that relation
between two is insignificant and not meaningful for investment perspectives.
Table-05 indicates correlation for two variables towards others that is positive and highly
significant except MC towards all. Covariance in Table-04 shows the relation is positive and
suggests two variables covariate with higher values of calculation and is completely insignificant
to form a proper meaning to standards of statistical values, as per their value increase and
decrease in investment market. Beta value in Table-04 suggests for existence of indirect
relationship in between MC and ROC that is -0.310 or -31% referring a reverse contribution of
ROC in increasing MC.
Table-04
Statistical Analysis for Ratio Relations
Analysis
Earnings per Share v/s
Share Price
Return on Capital v/s
Market Capitalization
Return on Equity v/s
Cash Dividend
Profit After-Tax v/s
Revenue/Sales
R Square
0.751
0.096
0.877
0.710
Adjusted R Square
0.715*
-0.055***
(0.860)**
(0.669)*
Covariance
1.702
3.484E23
0.073
0.292
Beta Coefficients
0.866
-0.310
0.937
0.843
t-value
4.592**
-0.799***
7.069*
4.140**
** p<=0.001; * p<=0.005; *** p>0.005;

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10.3 Return on Equity v/s Cash Dividend
The value of adjusted R Square is about 0.860 or 86% (Table-04) that indicates strength of
relation for independent variable (ROE) to dependent variable (CD); whereas only 12% is error
term which shows that ROE with some other market factors are combined determinants of CD in
investment market. The overall relation is significant at p<0.005 means relation between two is
meaningful to its formation in investment perspectives.
Table-05 indicates correlation for two towards others that is positive with highest of significance
level except MC. Covariance level in Table-04 shows dependency of two variables is positive
and suggests that two covariates with similar difference and space as per their value increase and
decrease in investment market. Beta value in Table-04 suggests existence of direct relationship in
between CD and ROE that is 0.937 or 93.7%, refers to contribution of ROE in creating more
value determination for CD in equity investment house.
10.4 Profit After-Tax v/s Revenue/Sales
The value of adjusted R Square for this relation is 0.669 or 66.9% (Table-04) that indicates
strength of relation for independent variable PAT to dependent variable R/S; whereas 33.1% is
error term which shows that just PAT is not overall determinant of R/S in investment market. It
is also significant at p<0.005 and is quite meaningful to its formation in investment perspectives.
Table-05 indicates correlation between two that is positive with highest of significance level
except towards MC. Covariance in Table-04 shows dependency of two variables is positive and
suggests that variables covariates (moves with similar difference and space as per their value
increase and decrease) in investment market. Beta value holds for existence of direct relationship
in between R/S and PAT that is 0.843 or 84.3% that refers to contribution of PAT in increasing
more R/S in investment.
11.0 Discussion
Investment decisions require application of empirical models to predict practicality of
determinants of an investment as nature of these decisions is highly concerned to present analysis
Table-05
Correlations for Determinants
Determinants
Earnings
Per Share
Share
Price
Return on
Capital
Market
Capitalization
Return on
Equity
Cash
Dividend
Profit
(After Tax)
Revenue
/Sales
Earnings Per Share
1.00
0.87*
0.97*
-0.30***
0.99*
0.96*
0.98*
0.91*
Share Price
-----
-----
0.92*
-0.03***
0.81*
0.88*
0.79*
0.93*
Return on Capital
-----
-----
-----
-0.31***
0.94*
0.98*
0.92*
0.93*
Market Capitalization
-----
-----
-----
-----
-0.38***
-0.44***
-0.44***
0.06***
Return on Equity
-----
-----
-----
-----
-----
0.94*
0.99*
0.87*
Dividend
-----
-----
-----
-----
-----
-----
0.94*
0.86*
Profit (After Tax)
-----
-----
-----
-----
-----
-----
-----
0.84*
Revenue/Sales
-----
-----
-----
-----
-----
-----
-----
1.00
* p<=0.001; ** p<=0.005; *** p>0.005;

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and future interpretation. The literature has revealed a list of factors that should be deemed in
forming the decision like economic factors influencing industry, company market operations
with performance trends and at all sector policy. Rest ahead at individual level consumption and
saving decisions are highly important. We find that optimal options for investment available
under uncertain conditions of Pakistan involve basic application of prescriptive decision theory
that is strict study of making decisions via statistical measurement and game theory in economics
for investment decision; whereby a flawless information is required to enforce an investment
decision to make a smart move that brings best in payoff for calculated odds of decision put-up.
It is just like utilizing a strategy to make an extensive study of the literature for investment
variables and go for the decision that minimizes upset (Dauben, 2006).
As fertilizer is a natural or artificial substance used to supplement soil to promote plant growth in
agriculture. The companies are trying to capture farmers who use their product, this is quite an
un-educated market and we have seen, do doubt each of the firm is at its best in educating their
target customers for selling and occupied a tremendous market share in national market.
Seasonal and cyclical flow in fertilizer sector is somehow irrational in Pakistan but its
performance for each one is best. Majority rule is in hands of FFC. Grouped investment can also
be a better option to investors to split risk factor. Certainly investment decisions frequently
involve extensive figures of money and most of them are complex to reverse and even can
influence investor’s personal strength of spending tolerance. Four corresponding relations
formed in this study are highly meaningful in providing best relationship with their significance
level that can even predict future growth of payoff for invested amount for investor.
We have found that most of investors look around the ratios and profitability figures in sector
and opt out statistical significance of variables but it is quite unpredictable. For instance, we find
that observing market capitalization of a company at its individual or jointly in a segment is
meaningful for investment decisions but note in Pakistan it is statistically not significant in
fertilizer sector. Therefore we must refer to expected rate-of-return that a company is enjoying
must be exceeding investor’s cost of capital. Combing all such as individual case study of three
leading firms, sector overall performance, statistical results for relations and their significance,
both of the hypotheses formed in this study holds true in Pakistan. The investors must properly
examine investment determinants with their statistical significance (Table-05) before making an
investment decision. No doubt, determinants of investment are significantly contributing to
investment decision. We also endorse discussion section with SWOT analysis for better
illustrating investment decision at last of study.
11.1 Sector Strength
The improving situation of Gas supply has improved production, distribution and sales line of
fertilizer industry for DAP and Urea supply to market. It is almost after a half decade of losing
the entire market gain from this sector is going to be transformed into profits this year, hope so
(Fertilizer sales looking up, 2015). Fertilizer sector has been given the priority over other sectors
for supply of gas by government side, as said by officials; as it is basic instrument of building

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nation’s backbone that is agriculture. Same was being directed to provincial attendants and
private firm’s representations to ensure distribution of fertilizer in each province on the basis of
their needs; government would completely support productivity continuation process and would
provide gas-priority to this sector (Ghumman, 2014).
Restriction in Gas supply has threatened the sector at large since last 5 years and that is what has
pushed producers and government to come on one platform to discuss and come up with the
solution of that. Both of parties have made a commitment to fulfill economic needs of nation by
contributing significant efforts, capital and productivity lines in fertilizer sector to boost
agriculture performance of country (Recorder, 2014).
11.2 Sector Weakness
A production loss of 2.7 million ton has been marked against overall available production
capacity of 6.9 million ton; suffering this loss government imported a significant quantity of urea
investing a marginal cost to satisfy the conditions. Future contracts have also been made in order
to fulfill the needs of agriculture based economy, showing a weakness of sector at now and this
may not prevail in future subject to commitment fulfillment by both.
11.3 Sector Opportunities
Facts and figures about productivity parameters, gaps for different timelines and different
periods highlight why shortcomings were on way to achieve planned results. A statement is also
made to save around 120 billion rupees if uninterrupted gas supply is given to this sector for
production purposes in forthcoming years. The learning can be obtained by viewing the growth
curves of Indian economy for policy definition and may be implemented in our economy
(Arifeen, 2013). It holds that demand is about 5.8 million tons against supply of 6.9 million tons,
which suggests that 1 million ton (if uninterrupted gas supply is there) can be exported to earn
significant figures of US dollars (Imaduddin, 2012).
11.4 Sector Threats
Less government concerns to this sector has pushed farmers to pay lesser attention and interest in
this sector for investment purpose. Negligence in economic policy each year, making barter
contracts against electricity with other countries would severely bring the trend of food shortage
in our domestic economy. The fact is that successful sectors must not be prioritized over back-
stayed sectors, so as to avoid inequality of resource allocation to discrete divisions; but
government has yet not understood this, they just try to encourage prosperous sector not back-
ones; and at last they begin to privatize for performance. A crucial attention is required to focus
on basic needs fulfilling firms (Hamid, 2013).
12.0 Conclusion for Investment Decision and Perceptions
It has been found in case study that the sector is set to bounce back for this year; the clouds of
uncertainties would be walking around; but the hope of new ray suggests for long-term
investment planning and implementation. The worst seems in quite improvement for Engro

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fertilizers in future, as its Enven plant and base plant has put into highest efforts of gaining
continuous supply of gas and that is now bind to Government and Mari gas to supply as per
terms and conditions settled. The loss in 2012 and slow earnings in 2013 were in the
consequences of Enven plant ran for just 45 days in 2012 and that prevails for two years in
profitability effect for Engro (Hyder & Jaffer, 2015). It is all thanked to Mari Gas continuous
supply that puts FFC at top most of industry norms, results and figures; While Fatima Fertilizer
has also a comparative competitive advantage to this; as they both have made all contracts with
Mari Gas and do not buy gas from government firms. Same sustainable advantage is also now
accessed by Engro for its good contribution value in market. The applicative contribution of
study holds true for both hypotheses.
We derive an investment decision priority as follows for investors to buy FFC shares at 1st,
Engro at 2nd, Fatima Fertilizer at 3rd; as per acceptance of risk factor. The good is that overall
joint industry investment can also be a favorable option to investors.
13.0 Limitations
The study is limited by time as per specific completion of coursework and sample selection size
(three leading firms involved in fertilizer sector) as per data access issues and concerns.
14.0 Future Directions
The future study can be expanded by widening scope of research as per investment of time
factor, more literature searching, changed empirical supporting and considering factors of
economic issues for policy making, increasing number of firms in sample size, using different
statistical techniques for specific results and taking multinational experts advice.

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SALU-CER December (2015)
39-49
Impact of Interest Rate and GDP Growth Rate on Inflation of
Pakistan (Time Series Analysis From 2005-2014)
Dr. Mohammad Masiullah Jatoi*, Safia Khan**
Abstract: - Inflation refers to the sustained increase in the aggregate or general price level in
any economy; that fluctuates because of the different economic factors. In this study two
independent variables (interest rate & GDP growth rate) and one dependent variable (inflation) is
designed to examine their impact. The hypotheses regarding the impact were made to determine
the significance between variables. This research work proved that there is significant impact of
interest rate & GDP growth rate on inflation that’s why both hypotheses cannot be rejected. Spss-
18 has been used for the interpretation of results by applying the technique of Linear Regression.
Inclusively statistical results recommended that interest rate & GDP growth rate is significantly
related with the inflation rate.\
Keywords: Interest rate, GDP growth rate, Inflation.
1.0 Introduction
Since, it has been known to the humans that there is scarcity of resources; nations are finding
more orderly ways to decide for their effective economic decisions, while keeping in view the
principle of zero tolerance in negligence of thrift habits and investment opportunities. In order to
make better and effective decisions and to know about how the economic mechanism functions
as a whole; the subject of economics suggests several factors to be kept in consideration.
Rising of prices for commodities would surely be a problematic situation for an economy, as its
cost would be to improve the income standards of the humans; less intake of foreign borrowing,
infrastructure investment decline and others, the short run results might be good but in long-run
it is not a good sign to prevail. While lower the inflation, would have somewhat better results in
long-run criteria, whereby the consistency of budgeting system provides a clear cut map of
defining a long term policy options in the economic zone, but in short-run it might not show
good results. The extra money that you pay back when you borrow money or that you receive
when you invest money is called interest. Keynes condemned the classical theories of interest on
ground to interest rate is determined neither through savings nor by modifies in the investment
directly.

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* Professor, Department of Business Administration, Shah Abdul Latif University Khairpur,
Sindh, Pakistan
** MS Scholar, Department of Business Administration, Shah Abdul Latif University
Khairpur, Sindh, Pakistan
He moralizes his has theory of interest recognized as ―Liquidity Preference Theory of Interest‖.
He sustains to interest rate is determined via the supply and demand of money. On the demand
side interest rate is administered through liquidity preference. On the supply side we have whole
supply of money accessible in the economy.
The GDP growth rate is the change in a nation’s GDP from one period of time to the next. This
is considered as the most essential measures of knowing the economic performance either well or
poor. Let us examine periodically from 2005 to 2014 to see how the Inflation rate of our nation is
surrounded by the inflammation of interest rate & GDP growth rate.
2.0 Literature Review
Leijonhufvud (1977), Howitt (1990), and Summers (1991); disputed the non-indexation of
classified accounting systems deforms reserves decisions and the distribution of capital beneath
elevated rate of inflation and, additionally, that inflation deflects talent left from actual
productive activity into take away socially productive economic activity designed plainly to
manage with or profit as of adjusts in the worth of money. These possible overheads of inflation
are not easy to quantify, we are not conscious of one attempt to approximate their special effects
on the trail of actual output.
Blanchard & Summers (1984); tinted the global scenery of interest rate raises, spotlighting on 6
large (OECD) economies. The majority of their scrutiny focused on short term rates, for the
reason that of require of procedures of predictable inflation over extensive time horizons
obligatory to build a determining of the long term actual bond rate. They formed an
approximation of the predictable inflation rate beginning the forecast of an easy auto regressive
model of real inflation and scrutinized modifies in four fundamental determinants: portfolio
preferences, saving, the expected effectiveness of investment, and monetary policy. They
accomplished that improved profitability and moves in the combine of fiscal monetary policy
were the key factors at the back the increase in actual rates. Ford & Laxton (1990); one more
study using the panel data, explained that an cumulative of (OECD) debt to GDP was a
momentous determinant of short term actual interest rates in associate countries and so as to
aggregate assess often removed the manipulate of own country debt. The outcome offered more
support intended for the sight of an included world’s capital market. Benabou (1992), Head &
Kumar (2005); the increase in price diffusion unpaid to inflation can moreover have actual
effects by raising the sum of resources committed to investigate on the division of buyers, as
highlighted in the look for theoretic literature. It will furthermore play a vital role in our
structure, which highlights the injurious effect of increasing price diffusion on business
breakdowns.
Ragan (1998); on the pragmatic side, there is almost no robust proof on relationship stuck
between inflation and actual outcomes. The journalism on the sound effects of tendency inflation
on the growth rates of productivity and has produced modest indication of an important impact,

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excluding in intense circumstances. Zafar & Murtaza (1998); verify a statistically affirmative
relationship stuck between macro aspects for the growth of economy of the Pakistan’s economy.
They discover that budget shortfall negatively influences the Gross Domestic Production of the
Pakistan’s economy and at same moment it manipulates positively the economy’s inflation.
Feldstein (1999); has falls out that dropping inflation commencing 2percent toward 0 would
move up productivity by 4 to 6 percentage peaks for the reason that of the non-indexation of
principal income taxation. Though, this upshot appears more similar to a dilemma to be packed
with by tax establishment than private bankers.
Vanish (1999);according to inflation is continued increase in the common price level taken as
regards through elevated rate of increase in the total money supply. Inflation appears in economy
on description of the raise in money returns of assured segments of economy lacking any
consequent raise in their output, generous rise to a raise in the collective demand for services and
goods which can’t be gathered at the present prices by total existing supply of services and goods
in economy.
Malik & Chowdhury (2001);performed co-integration study of the inflation on the economic
growth used for 4 South Asian countries (Pakistan, Bangladesh, Srilanka, and India) and details
two attractive points. First, economic growth and inflation are absolutely related. Second, the
sympathy of the inflation to adjust in growth rate is bigger than that to amends in inflation rate.
One latest analysis recommends s that nearby is an entrance intensity of inflation in correlation
between inflation and output growth. Hamilton (2001); inflation has been commonly described
while an economic circumstances where raise in money supply is more rapidly than the modern
manufacture of latest services and goods in similar economy. Sellin & Peter (2001); the
Keynesian economist indicates that amend in money supply will instantly influence on stock
prices barely if the amend in money supply increase probability about potential monetary policy.
According to those economists, optimistic money supply bump into that will guide people to
predict the tapering monetary policy in future. They teach for finances in expect of tightening of
the money supply in future which will move forward the recent rates of interest. Ryan (2001);
the Federal Reserve offered data on the ranks of (M1 and M2) on weekly base it has been
assembling data on money supply since 1950s. In the fewer financially scrambled world that be
composed then, the money supply proved a very muscular relationship to how greatly money
was exhausted it was consequently studied by economist for ideas to economic growth.
Constitution approved in 1978 with the purpose of structured Federal Reserve toward set annual
objectives for the growth of money supply. At the point in time, there was still high link between
growth of money supply and growth of primarily economy as calculated by (GDP) gross
domestic product.
Fernando, Rober, & Warren (2001);the marvelous rule of this agreement is that the methods of
the monetary policy have to be short- term interest rates that the policy should be crucial point on
the supremacy of inflation, that inflation may be abridged by rising short- term interest rate.
These suggestions are taken while known would appear to engage the elimination of quantity
theory of money, these theories that near the inflation rate can be proscribed by scheming the
money’s rat growth. Such a refusal is a complicated step to acquire because the customary
exhibition that continue connecting with inflation, monetary policy, and interest rate there is a
too much amount that be proposes almost rightly of proof that raises in average rate of the
growth of money that are interrelated with equal raises in average rates of inflation and in rates

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of interest. Due to the quantity theory, speedy growth of money is well-known attribute of
monetary satisfaction; it is interrelated with high rates of interest as well as with high rates of
inflations.
Karanassou, Sala, & Snower (2003); empirically scrutinized the long-run trade off stuck between
unemployment and inflation by use (Panel Data Study) in favor of European countries. They
empirically originate that long-run trade off stuck between unemployment and inflation does stay
alive in casing of the European countries. Gokal & Hanif (2004); analysis several dissimilar
economic theories to develop compromise on the growth and inflation relationship used for the
Fiji’s economy. Their results prove that a fragile negative relationship survives between growth
and inflation, while adjust in production gap tolerates significant bearing. The causality stuck
between two variables run one-way from gross domestic production growth toward inflation.
Shamim & Murtaza (2005); investigated the connection between economic growth and inflation
in the background of Bangladesh. The empirical proof expresses that there subsists statistically
important long run negative link between economic growth and inflation for country as specified
by statistically important long run negative link between real GDP and CPI.
3.0 Research Model
4.0 Research Hypothesis
H1: Interest rate is positively related with inflation.
H2: GDP growth rate is positively related with inflation.
Data set (2005-2014)
Year
Inflation rate
Interest rate
GDP Growth Rate
2005
9.08%
9.00%
8.96%
2006
7.91%
9.50%
5.82%
2007
7.58%
10.00%
5.54%
2008
20.15%
15.00%
4.99%
2009
13.94%
12.50%
0.36%
2010
13.85%
14.00%
2.58%
2011
11.97%
12.00%
3.62%
2012
9.73%
10.00%
3.84%
GDP Growth
Rate
Interest Rate
Inflation

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2013
7.68%
10.00%
3.70%
2014
7.23%
9.50%
4.14%
Sources: *State Bank of Pakistan *Ministry of Finance
5.1 Methodology
5.1.1 Data Collection Method:
Secondary data collection method was used for the collection of data regarding overall inflation,
interest rate and GDP growth rate, from state bank of Pakistan and entered in the SPSS 18 for
applying linear regression to check the inter relationship between the variables mentioned above
to predict the GDP growth rate and interest rate.
5.1.2 Diagnostic Test:
I = α + IRβ + GDPβ + µ
6.0 Results and Discussions:
6.1 Regression Analysis:
Model Summary
Model
R
R Square
Adjusted R
Square
Std. Error of the Estimate
d
i
m
e
n
s
i
o
n
0
1
.951a
.905
.878
1.44230
a. Predictors: (Constant), GDP Growth Rate, Interest Rate
b. Dependent Variable: Inflation Rate
ANOVA(Table 2)
Model
Sum of
Squares
df
Mean Square
F
Sig.
1
Regression
138.570
2
69.285
33.306
.000a
Residual
14.562
7
2.080
Total
153.131
9
a. Predictors: (Constant), GDP Growth Rate, Interest Rate
c. Dependent Variable: Inflation Rate
The Adjusted R Square indicates the overall fitness of the model and the rest is error term. In
this study, the value of adjusted r square in (Table 1) is about 0.878,which shows 87.8%
contribution of independent variables (Interest rate and GDP growth rate) to the dependent
variable (Inflation).The error term is about 12.2% and the research model is fit at the
significance level of 0.000 in (Table 2).
Coefficients
Model
Unstandardized Coefficients
Standardized
Coefficients
T
Sig.
B
Std. Error
Beta
1
(Constant)
-13.272
3.596
-3.690
.008
Interest Rate
2.029
.262
1.031
7.730
.000
GDP Growth Rate
.359
.244
.196
1.467
.186
a. Dependent Variable: Inflation Rate

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In (Table 3), value of Beta indicates that there is direct relationship between dependent
(inflation) and independent (interest & GDP growth rate) variables.
7.0 Conclusions
This study explores the impact of interest rate and GDP growth rate on inflation of Pakistan from
2005 to 2014.Pakistan’s economy is facing economic challenges day by day that are why the
economic performance is unstable. Inflation has both the positive and also negative effect on
economy. This research work is carried out to examine the fluctuation in inflation rate because of
interest & GDP growth rate. The results suggested that both independent variables have
significant or direct relationship with the dependent variable inflation rate which can be
controlled by prudent policies.

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