Article Type: Research Article Article Citation: Professor Dr. Md. Abdus Sabur,
Md. Nazmul Huda, and Professor Dr. Md. Abu Sina.
(2020). FACTORS AFFECTING PROFITS RELATING TO PURCHASE AND SALES: A STUDY ON
TITAS GAS TRANSMISSION & DISTRIBUTION COMPANY LIMITED. International
Journal of Research -GRANTHAALAYAH, 8(7), 391-400. https://doi.org/10.29121/granthaalayah.v8.i7.2020.774 Received Date: 15 July 2020 Accepted Date: 31 July 2020 Keywords: Profits Purchase Sales Titas Gas Transmission Distribution Company Limited
JEL
Classification: L-95 The present study is an attempt to find out the factors affecting profits relating to purchase and sales of Titas Gas Transmission & Distribution Company Limited. The objectives of the study are to overview the affecting factors on profits, to determine the important factors that affect on profit relating to purchase and sales and to provide some suggestions and recommendations to enhance the profits. Correlation and regression have been applied to analyze the data. It is estimated that commercial, fertilizer and CNG are the most important factors to drive the profit both for the cases of purchase and sales. These three factors collectively explained the total variance of gross profit by 96.6 percent and 96.8 percent for the situation of purchase and sales respectively. The suggestions and recommendations are given to emphasize the purchase and sales on the identified factors to enhance the benefits of the company.
1. INTRODUCTIONBangladesh is a developing country. The development of a
country depends on uniform supply of power and energy that ensure the
production levels of all sectors. The mining resource related to natural gas is
one of the most important sources of generating power and energy. The mining
source that has yet been discovered natural gas is one of the most remarkable
resources of Bangladesh. In the power sectors power generation and captive
power of Bangladesh are mostly depended on the sources created from
predominantly oil and gas. Oil is to be imported from foreign country but gas
is collected locally from available local mining resources. For this reason gas
sector is the very important alternative source of energy. Most of the
fertilizer industry, CNG station, industry, commercial factory, bricks field
and household utilize gas frequently. In the year 7017-2018, 968.7 2. STATEMENT OF THE PROBLEMThe company has been playing a vital role in the development of the country through the contribution of creating energy and power that helps to run the machineries of industry, commercial activities, agricultural activities and household affairs. The sustainable developments of the mentioned sectors depend upon mainly successful purchase and sales operations of gas of the company. The Company Ltd is operating as the Transmission and Distribution Company both internal and external of Bangladesh. Company is purchasing gas directly from gas field like Hobigonj gas field, Shahazibazar gas field, Norsingdhi gas field, Kamta gas field and Rupgonj gas field etc. where both of the transmission and distribution activities are conducted. There are some remarkable problems that may herm the successful operations under the activities of purchase and sales of the company. 3. OBJECTIVES OF THE STUDY
The main objective of the study is to identify factor affecting profits relating to purchase and sales of Titas Gas Company Limited. For achieving the main objective some specific objectives are presented as follows: ·
To overview
the affecting factors on profits relating to purchase and sales of Titas Gas Transmission and Distribution Company Limited; ·
To determine
the important factors that affect on profit relating
to purchase and sales of Titas Gas Transmission and
Distribution Company Limited over the study period under review; and ·
To provide
some suggestions and recommendations to enhance the profits of the company
regarding purchase and sales. 4. REVIEW OF RELATED LITERATURE
Some literatures relating to the topic are reviewed
for finding out the research gap as follows: Shawan and Maksud (2015) stated the operational, marketing and financial performances of Titas gas company Ltd. based on five years data to determine the current position, influential risk factors for consistent growth and contribution in the development of national economy, providing some suggestions as to make policies for the improvement of customers services, reduction of system loss and realization of account receivables for continuation of the reputation. Baratil and Sepasgozar (2015) conducted a study on’’ Factors Affecting on Productivity of Oil and Gas Construction Projects: An AHP (Analytical Hierarchical Process) Analysis”where itis shown that management factors are the important factors which affect the productivity of the oil and gas construction project and project’s factors do not have significant effect on productivity. Asaduzzaman & et al (2015) measured the
financial performances of LPG Gas Ltd after restriction of installation of new
pipe line and before and after the govt. restrictions of new gas connection in
households from July
2009 to until due to a gas shortage in the country. Shamsuzzoha (2017) stated that TGTDCL is responsible for distributing natural gas to its customers. This study shows the management should reduce the bureaucratic system, delegating both financial and administrative power, improving professionalism, introducing integrated computer system which will help to efficient customer services. It has been found from the above literature review that a number of studies have been carried out by many researchers. Some researchers have drawn their attention on the performance measurement, management systems, and financial analysis of gas sectors. No works like Factors Affecting on Profits Relating Purchase and Sales: A Study on Titas Gas Transmission & Distribution Company Limited has been yet been done regarding the under taken topic. By the right use of the research results, the company as well as the policy maker, the interested researcher in this field can be benefited a number of information is available and they are very easy to create and share. The concern authority should apply them while functioning in this sector. On the basis of above reviews it is found that there is no
research work has been done on identifying the factors affecting profit
relating to purchase and sale. There lies a research gap. So for fulfilling the
research gap the researchers have selected the topic "Factors Affecting
Profits Relating Purchase and Sales: A Study on Titas
Gas Transmission & Distribution Company Limited 5. METHODOLOGY OF THE STUDY
To find out the factors affecting profit relating to
purchase and sales of Titas Gas Company Limited only
secondary data are used. Data are collected from the enlisted stock market that covered
the period 2009-2019 of the study. The collected data and information
have been compiled to estimate the gross profit, Govt. power, private power,
fertilizer, industry, captive power, CNG, commercial and domestic for each of
purchase and sales amount for each of the year under study and to analyze by
using statistical tools and techniques like correlation and regression with the
help of SPSS Version-22. Collected data are limited to purchase and sales
volume which confined within some important categories of customers. However
the gross profit depends on the enrolment of these main sorts of customers. For
identifying relation between profit and different variables relating to
purchase & sale the following hypothesis has been formulated for the study: H0:1 There is no positive relation for each of the purchase and sales related variables with the profit of the company for the period under study. 6. CONCEPTS OF RELATED TOPICPurchase: Purchase is the acquisition by the payment of money or its equivalent; buying, or a single act of buying (dictionary.com, LLC). Sales: A sale is a transaction between two or more parties in which the buyer receives tangible or intangible goods, services, or assets in exchange of cash or promised to pay at a later. Seller makes sales with a view to generating income (Hermanson & et. al, 1998) Gross Profit: Gross
profit is the profit a company makes after deducting the costs associated with
making and selling its products, or the costs associated with providing its
services. The gross profit of a company is the total sales
of the firm minus the total cost of the goods sold. The total sales are all the
goods sold by the company. The total cost of the goods sold is the sum of all
the variable costs involved in sales (Business Encyclopedia). The Multiple-regression: Multiple-regression is a statistical
procedure in which a dependent variable (Y) is modeled as a function of more
than one variable (X1, X2, X3… Xn). The population multiple-regression model
may be written as: Y= where ( ) is the intercept and other are the slope terms
associated with the respective independent variables. In this model,represents the population error term, which is the difference
between the actual Y and that predicted by the regression model (). The ordinary least-squares (OLS) criterion for the best
multiple-regression model is that the sum of squares of all the terms be
minimized (Gupta, 2007). Variance Inflationary
Factors (VIF): The application of multiple regressions involves the
possible multi co-linearity of the explanatory variables. This condition refers
to situations n which some of the explanatory variables are highly correlated
with each other. In such cases, the values of the regression coefficients for
the correlated variables may fluctuate drastically, depending on which
variables are included in the model. One method of measuring co-linearity uses
the variance inflationary factor (VIF) for each explanatory variable. This VIF
is defined as follows: VIF = Where, R2 represents the coefficient of multiple determination of explanatory variable X with all other x variables. If a set of explanatory variables are uncorrelated, then VIF will be equal to 1. If the set were highly Inter-correlated, then VIF might even exceed 10. However, other researchers suggest a more conservative criterion that would employ alternative to least-squares regression if the maximum VIF were not to exceed 5 (Lind, Marchal& Mason, 2002). Correlation: Correlation Analysis is a statistical technique used to indicate the nature and degree of relationship existing between one variable and the other(s) (gupta,2007). 7. ANALYSIS AND INTERPRETATIONSTo find out the impact of important factors on dependent variable it is essential to prove the hypothesis and to sort out the analysis of data for the study as follows: H0: There is no positive association for each of the purchase and sales related variables with the profit of the company for the period under review. Table 1: Pearson’s Correlations of Profit with Purchase and Sales Related Variables of Titas
Source: N=10, Compiled
From secondary data, *Correlation is significant at the 0.05 level (2-tailed), **Correlation is significant at the 0.01 level (2-tailed). Table No. 1 indicates the pearson’s correlations of profit with purchase and
sales related variables of Titas Gas Company where purchase has the positive
correlation with each of the factors Power (gvt.),fertilizer and commercial by the degree of
0.166, 0.813** and 0.724* respectively on the other hand it has negative
correlation with rest of the factors. At the same time the sales has the positive
correlation with each of the factors Power (gvt.), fertilizer and commercial by the degree of
0.195, 0.806** and 0.764* respectively on the other hand it has negative
correlation with rest of the factors. Thus, the null hypothesis is accepted for
each of the factors Power (gvt.), fertilizer and commercial in both of the situations
of purchase and sales while the hypothesis is rejected for each of the factors Power
(pvt.), Industry, Cap. Power, CNG and domestic. Thus, it is conclude that the
factors Power
(gvt.), fertilizer and commercial shows the positive impact on profit and Power
(pvt.), Industry, Cap. Power, CNG and domestic indicate the negative impact on
profit. Regression
Analysis To have a better clarification the statistical tools multiple
regression analysis is applied to analyze the data and the obtained results are
shown as below: Table 2: Model Summary for Purchase Related
Variables of Titas
Source: Compiled from secondary data by SPSS version: 22, Dependent Variable: Gross profit, Predictors: (Constant), Fertilizer, CNG and Commercial. Table no. 2 shows the model summary for purchase related variables of Titas where the predictor variables are Fertilizer, CNG and Commercial collectively explained by 96.6 percent of the dependent variable gross profit. Moreover Multiple R, R-Square Adjusted R-Square and Std. Error of the Estimate are found to be 0.996, 0.993, 0.900 and 0.928 indicating quite a respectable result for well fit of model to the undertaken study. ANOVA Test Table 3: ANOVA-Test for Purchase Related Variables of Titas
Source: Compiled from secondary data by SPSS version: 22, Dependent Variable: Gross profit, Predictors: (Constant), Fertilizer, CNG and Commercial. The above table shows that P-value is significant (0.00), so null hypothesis is rejected at 0.00 percent level of significance. On the basis of this analysis it is found that there exists a significance relationship between the population mean and the sample mean indicating the model is the best fitted for the study under review. The Model of the purchase related factors is as below: Gross profit = 1530.50 + 0.44(Fertilizer)
-2.82(CNG) +8.83(Commercial) +0.928 Table 4: Coefficients for Purchase Related Variables of Titas
Source: Compiled from secondary data by SPSS version: 22, Dependent Variable: Gross profit, Predictors: (Constant), Fertilizer, CNG and Commercial. The measurements of the coefficients for purchase related variables of Titas have been depict in the above Table No. 4 where the Gross profit was taken as dependent variable and the independent variables were Fertilizer, CNG and Commercial under the study period. These mentioned variables above were extracted from eight independent variables as influential contribution to the dependent variable. The selected independent variables Fertilizer, CNG and Commercial were found to be statistical significant at 0.07 percent, 0.01 percent and0.04 percent level of significant respectively. In the model, variance inflationary factors (VIF) were found from to be the lower of 1.41 to the highest of 1.93 indicates expected extend of multicollinearity. The coefficient of the predictors Fertilizer and Commercial had positive impact but CNG shows the negative effect on the dependent variable gross profit. On the other hands, unique and significant impacts on the dependent variable have been shown by the dependent variables CNG and Commercial. Table 5: Model Summary for Sales Related Variables of Titas
Source: Compiled from secondary data by SPSS version: 22, Dependent Variable: Gross profit, Predictors: (Constant), Commercial, Fertilizer and CNG. Table no. 5 shows the model summary for sales related variables of Titas where the predictor variables are Commercial, Fertilizer and CNG, collectively explained by 96.8 percent of the dependent variable gross profit. Moreover Multiple R, R-Square Adjusted R-Square and Std. Error of the Estimate are found to be 0.998, 0.938, 0.907 and 88.80 indicating quite a respectable result for well fit of model to the undertaken study. Table 6: ANOVA-Test for Sales Related Variables of Titas
Source: Compiled from secondary data by SPSS version: 22, Dependent Variable: Gross profit, Predictors: (Constant), Commercial, Fertilizer and CNG. The above table shows that P-value is significant (0.00), so null hypothesis is rejected at 0.00 percent level of significance. On the basis of this analysis it is found that there exists a significance relationship between the population mean and the sample mean indicating the model is the best fitted for the study under review. The Model of the sales related factors is as below: Gross profit = 1592.41 + 0.44(Fertilizer) -3.04(CNG) +9.51(Commercial) + 88.80. Table 7: Coefficients for Sales Related
Variables of Titas
Source: Compiled from secondary data by SPSS version: 22, Dependent Variable: Gross profit, Predictors: (Constant), Fertilizer, CNG and Commercial. The measurements of the coefficients for sales related variables of Titas have been shown in the above Table No. 7 where the Gross profit was taken as dependent variable and the independent variables were Fertilizer, CNG and Commercial under the study period. These mentioned variables above were extracted from eight independent variables as influential contribution to the dependent variable. The selected independent variables Fertilizer, CNG and Commercial were found to be statistical significant at 0.05 percent, 0.00 percent and0.02 percent level of significant respectively. In the model, variance inflationary factors (VIF) were found to be the lower of 1.41 to the highest of 2.05 indicates expected extend of multicollinearity. The coefficient of the predictors Fertilizer and Commercial had positive impact but CNG shows the negative effect on the dependent variable gross profit. On the other hands, unique and significant impacts on the dependent variable have been shown by each of the dependent variables included in the model. 8. CONTRIBUTION TO NATIONAL EXCHEQUERTitas Gas Company is a profitable organization in Bangladesh. The earned profit is playing an important role in the national economy to the national Exchequer through payment of custom duty (CD), Value Added Tax (VAT), Corporate tax, Dividend (75%) and DSL (Debt Service Liabilities). It is also known that TGTDCL is the highest tax payer in the energy sectors in Bangladesh. During the study period the contribution to national exchequer has been shown in the following table No. 8: Table 8: National payment to government of Titas Figure in Crore Taka
Sources: Annual Reports of Titas Gas Transmission and
Distribution Company Ltd. During 2010-2018. 9. DRAW BACKS9.1. DRAWBACKS IN PURCHASINGThe major drawbacks of the Titas Gas Transmission and Distribution Company Ltd. in case of purchasing are (website of Titas Gas Co.): 1) No inlet metering system from the purchase of gas from GTCL: TGTDCL purchases gas from gas field and GTCL. When gas is purchased from gas field there is inlet metering system and out let metering system but no inlet metering system in GTCL. So, there is drawback what amounts of volume actually purchased from GTCL are not ensured. 2) Leakage in the pipe line: The accounting life of pipeline is 20 years but most of the pipe line are old but is used. There is leakage in pipe line and system loss is incurred. 3) Low pressure in transmission line: Sometimes pressure of gas in the pipe line is low due shortage of gas production. It is also a problem that volume of gas is not accurate in that case. 4) Gas turned into condensate: When the temperature is low, gas turned in condensate as like as oil. 5) Problem relating to failure of compressor: The main activities of compressor are heating the gas and ensure the supply of gas. If compressors fail there is a disorder in supply of gas which is a vital problem. 9.2. DRAW BACKS IN SALESTitas Gas Transmission and Distribution Company Ltd. distributes the purchased gas to its customers like power station, fertilizer factory, captive power, industry, commercial, CNG etc. at the time sales there are some drawbacks which are given below: 1) Illegal gas connection: Some customers are engaged in taking illegal connection by pass line, unauthorized load etc. Consequently, misuse is occurred and profit is lessened. 2) No Metering: There is any metering system in most of household’s customers. So, they can consume unlimited gas. 3) Shortage of Gas: Shortage of gas supply due to misuse of the customers is a great problem of the company. 4)
Poor
customer’s services: Customer service is not available frequently. For this
reason, the customer handles the system as per their desires. 5) Bad debts: Huge amount of bad debts are occurred that harms the uniform sales. Consequently, profit is deteriorated. 10. CONCLUSIONIt is concluded that the factors power (gvt.), fertilizer and commercial show the positive impact on profit and power (pvt.), industry, captive power, CNG and domestic indicate the negative impact on profit. The model of the both situation- purchase and sale estimates the factors fertilizer, CNG and commercial of which fertilizer, and commercial have positive significant impact on profit of the company but CNG has the negative impact on the same. 11. RECOMMENDATIONSOn the basis of the findings of the research work and the
observations of the researchers the following suggestions are recommended for
the betterment of the company: 1) More attention should be given to hold the better position in the situation of the factors power (gvt.), fertilizer and commercial in all respects of purchase and sales of gas; 2) Purchase and sales should be concise in the reasonable positions so the factors power (pvt.), industry, captive power, CNG and domestic are able to provide positive impact on profit; 3) Inlet metering system and outlet metering system should be introduced and strictly maintained and controlled by the company; 4) Replacement of old pipeline should be done to overcome the misuse of gas from the leakage through pipeline; 5) Gas production should be improved to maintain uniform pressure in the gas pipeline; 6) Compressor and heating systems should be improved to maintain uniform pressure in the gas pipeline; 7) Illegal gas connections should be stopped by the proper supervision of the company; 8) Metering system for all household customers should be introduced to overcome the misuse of gas; 9) Customers services should be improved by uniform supply of gas; and 10) Huge amount of bad debts should be reduced to enhance the uniform sales and profit. SOURCES OF FUNDINGThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. CONFLICT OF INTERESTThe author have declared that no competing interests exist. ACKNOWLEDGMENTNone. REFERENCES
[1]
Ahmed,
R. & Akib, M. H. (2018). Evaluation of well performance of Titas gas field
by decline curve analysis using type curves. Journal of Nature Science and
Sustainable Technology, Volume 12, Number 2, Nova Science Publishers, Inc.
[2]
Al-Fattah
S. M., & Startzman R.A. (1999). Analysis of worldwide natural gas
production. Society of Petroleum Engineers, SPE 57463, SPE, Texas A&M
University. Copyright 1999, Society of Petroleum Engineers Inc.
[3]
Asaduzzaman,
M. and Kawsar, H. M. (Feb, 2015). Financial performance analysis of LP Gas Ltd.
with special reference to Govt. restriction on New Piped Gas Connection to households. International Journal of Business
and Technopreneurship and Development Studies, Volume 5, No. 1, pp. 49-60
[4]
Barati1,
K. & Sepasgozar S. M. E. (2015). Factors affecting on productivity of oil
and gas construction projects: An AHP analysis. American Journal of Civil
Engineering and Architecture, Vol. 3, No. 1, pp. 21-27. Available online at
http://pubs.sciepub.com/ajcea/3/1/4, Science and Education Publishing.
DOI:10.12691/ajcea-3-1-4
[5]
Bello,
U. & Sabo, H. A. (2018). The impact of lease capitalization on
profitability of Nigerian oil and gas industry. Faculty of Humanities,
Management and Social Sciences, Department of Accounting and Business
Administration, Federal University, Kashere, Gombe State.
[6]
Daryanto,
W.M. & Nurfadilah, D. (2018). Financial performance analysis before and
after the decline in oil production: Case study in Indonesian Oil and Gas
Industry. International Journal of Engineering & Technology, 7 (3.21).
www.sciencepubco.com/index.php/IJET.
[7]
Erdoğan,
E. O., Erdogan, M., and Omurbek, V. (2015). Evaluating the effects of various financial ratios on company financial
performance: Application in Borsa stanbul, Business
and Economics Research Journal, Volume
6, Number 1. pp. 35-42. www.berjournal.com
[8]
Germaine,
D. & Kruger, J. (December, 2017). Determinants of oil price influence on
profitability performance measure of oil and gas companies: A panel data
perspective. International Journal of Economics, Commerce and Management,
United Kingdom. Vol. V, Issue 12, Licensed under Creative Common Page 993.
http://ijecm.co.uk/
[9]
Gupta S.
P. & Gupta M. P. (2007). Business statistics. Fourteenth Enlarged Edition,
New Delhi, India: Sultan Chand & Sons.
[10] Hermanson, G. H., Edwrds, J. D. & Maher,
M. W. (1998). Accounting: A business perspective.
[11] Seventh edition, Manchaster, USA: Irwin
McGraw-Hill.
[12] Kalam, A., Zakir, H. M., &Rana, M.M.
(2013). Performances evaluation of Selected Commercial Banks in Bangladesh, Journal
of Faculty of Business Administration (JFBA) The Islamic University Studies (Part-C) Vol-10, No-1 PP
81-98
[13] Kosmidis, K. & Stavropoulos, A. (2014).
Corporate failure diagnosis in SMEs: A longitudinal analysis based on
alternative prediction models.
International Journal of Accounting & Information Management, Vol.
22, No. 1, pp. 49-67.
[14] Kothari, C. and Garg, G. (2014). Research
methodology- Methods and Techniques. 3rd edition. New Delhi, India: New Age
International (P) Ltd., p.63.
[15] Lind. Douglas A., Marchal, William G. and
Mason, Robert D. (2002). Statistical techniques in business & Eeconomics.
New York, USA: The McGraw-Hill Companies, Inc.
[16] Putra, A. P., Lahindah, L. & Rismadi, B.
(2012). Financial performance analysis before and after global crisis (Case
study in Indonesian oil and gas sector for the period of 2006-2011). Rev.
Integr. Bus. Econ. Res., Vol. 3(1), PP. 42-51.
[17] Shamsuzzoha, M. (2017). Service procedure of
TGTDCL, is it compatible with the modern world? -A case study of TGTDCL.
Proceedings of the 2017 International Conference on Industrial Engineering and
Operations Management (IEOM).
[18] Shawan, M. U. & Maksud, A. S. M. (2015).
Performances of Titas Gas Limited and managerial challenges, International Journal of Enterpreneurship and
development studies, Vol-3 No-2.
[19] Singh, Y. (2015). Fundamental of research
methodology and statistic. New Delhi: New Age International (P) Ltd.
Publishers, p. 88.
[20] Wang, Y. J. (2014). The evaluation of
financial performance for Taiwan container shipping companies by Fuzzy TOPSIS,
Applied Soft Computing, 22, pp. 28–35. WEBSITES
[1]
Business
Encyclopedia, https://www.shopify.com/encyclopedia/gross-profit, Retrieved on
July 15, 2019.
[2]
www.titasgas.org.bd,
Retrieved on July, 15, 2019.
[3]
https://www.dictionary.com/browse/purchase-
Retrieved on July 05, 2020.
[4]
https://www.titasgas.org.bd/temp/source/Titas%20AR_2013-14.pdf,
Retrieved on July 15, 2019.
[5]
https://www.titasgas.org.bd/temp/source/TITAS_AR_2014-15.pdf,
Retrieved on July 15, 2019.
[6]
https://www.titasgas.org.bd/temp/source/TITAS%20AR_2015-16.pdf,
Retrieved on July 15, 2019.
[7]
https://www.titasgas.org.bd/temp/source/AR201617.pdf,
Retrieved on July 15, 2019.
[8]
https://www.titasgas.org.bd/temp/source/AR201718.pdf,
Retrieved on July 15, 2019.
[9]
http://petrobangla.org.bd_2018.pdf,
Retrieved on July 15, 2019.
[10] http://bbs.portal.gov.bd¬_2018.pdf, Retrieved
on July 15, 2019.
[11] http://petrobangla.org.bd_2019.pdf, Retrieved
on July 15, 2019.
This work is licensed under a: Creative Commons Attribution 4.0 International License © Granthaalayah 2014-2020. All Rights Reserved. |