ISSN: 2958-2776
Vol.: 03 Issue: 01 January-June 2024
Journal of One Initiative Research and Development
an international multidisciplinary journal
©OIRD 1
Technological Integration Impacts on Fish Supply Chain in
Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder*
*Shahidur Rahaman Mazumder, MPhil Fellow, Bangladesh University of Professionals, Email:
[email protected]
Abstract
The fishery industry has one-fourth of the agricultural sector's contribution to
the GDP. However, the fishery industry has been facing several challenges
during fish trading that adversely impact Bangladesh's fish supply chain. The
main objective of this research is to find the impact of technological integration
on Bangladesh's fish supply chain. Additionally, this study explores the effects
of technology integration on the unjustified middleman gain in Bangladesh's
fish supply chain. This study uses secondary cross-sectional data to conduct
estimation, i.e., descriptive and quantitative analysis (Ordinary Least Squares
and Logistic Regression). Regarding the estimated results, the technology-
integrated supply chain, twoG and threeG mobile connection, may have a
mixed impact on the fish supply, where the twoG mobile connection may have a
positive effect, and the threeG mobile connection may negatively impact the
middleman gain and inland fish production in Bangladesh. However, the twoG
connection may increase, and the threeG connection may reduce the presence
of unjustified gain from Bangladesh's fish supply chain. By addressing these
issues, this study suggests several recommendations and concludes that
collaborative efforts and strategic planning can enhance the inland water fish
productivity, efficiency, and sustainability, and adaptation of modern
technology integrated fish supply chain may positively impact Bangladesh's fish
supply chain and minimize Bangladesh's fishery industry's unwanted activities
of intermediaries.
Key Words: Technology integration, Bangladesh, Fish supply chain, Ordinary
Least Squares, Logistic Regression.
JEL Classification: M3, Q1, N7, O3
Article Info:
Received: 10 December 23
Accepted: 15 March 24
Research Area: Supply Chain Management
Table: 06
Author's Country: Bangladesh
1.0 Introduction
The agricultural sector of Bangladesh
has a significant contribution to GDP.
According to BBS (2021), the
contribution of the agricultural sector
to GDP was 12.07% in the fiscal year 2020-21. Most importantly, fisheries, and
major subsector of Bangladesh agriculture, accounted for 2.64% of GDP and
grew by 4.11% in the same fiscal year. This subsector constitutes around one-
Technological Integration Impact on Fish Supply Chain in Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder
©OIRD 2
fourth of the agricultural sector. The fish and fishery products brought in 1.39%
of total export earnings in 2020 (BER, 2020). More than 12% of the population is
engaged, directly and indirectly, in several activities in the fisheries sector for
their livelihood. Meanwhile, Bangladesh has already achieved self-sufficiency in
fish production and fish consumption. Reportedly, it ranked third in inland open-
water production and fifth in aquaculture fish production globally (FAO, 2020).
Besides, fish consumption per person per day in this country was 62.58 grams,
against the targeted consumption of 60 grams (BBS, 2016).
Fishes are mainly collected from inland and marine fisheries, which can be
classified into twelve sources, i.e., River, Pond, Floodplain/Haor, Beel, Baor,
Shrimp farm, seasonal CWB, pen and cage, Kaptai lake, the Sundarbans, Marine
industrial and artisanal. Department of Fisheries Bangladesh concluded in the
fisheries statistics of Bangladesh in the 2021-22 fiscal year (Fishery Department,
2021-22) that Bangladesh is one of the leading fish producers in the world, with a
total production of 4.759 million metric tons in FY 2021-22, along with inland
open water (catch) accounting for 27.78 percent (1.322 million metric tons) and
inland closed water (culture) accounting for 57.39 percent (2.731 million metric
tons). Inland fisheries produce 85.10 percent of total fish production. More
precisely, inland capture and culture fisheries grew at the rates of 1.03 and 3.83
percent, respectively, in the 2019-20 fiscal year. In contrast, marine fisheries
production was 0.671 million metric tons, with a 14.90 percent contribution to
overall fish production and a growth rate of 1.70 percent. In the 2019-20 fiscal
year, the overall growth rate of total fish output was 2.72 percent. Inland
aquaculture's overall growth performance showed a moderately rising trend. Over
the last 37 years, fish production has increased almost six times (0.754 million
metric tons in 1983-84 to 4.503 million metric tons in the 2019-20 fiscal year).
Though the country achieved revolutionary success in fish production, the lack of
a technology-integrated supply chain emerged as a serious deterrent. The main
objective of this study is to explore the benefits of technology integration in
Bangladesh's fish supply chain.
A supply chain is a network that connects a firm and its suppliers in order
to manufacture and deliver a particular product to the final consumers. Different
activities, people, entities, information, and resources are all parts of this supply
chain network. The supply chain also depicts various stages through which a
product or service flows from its initial state to its destination. Companies create a
supply chain network to decrease production costs and maintain a sustainable
competitive position in the marketplace. Technology integration helps to offer
visibility and control across the whole supply chain system so that data-driven
choices can be made in real-time regarding everything from inventory status,
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manufacturing slowdowns, and supplier shortages to logistics, transportation,
delivery schedules, pricing changes, and more (Patel, 2021). Saurabh and Dey (
2021) reported that the efficiency and quality control of the agri-food supply
chain could be increased by applying such technologies as blockchain, the
Internet of Things (IoT), wireless sensor networks, cloud computing, and machine
learning. Yet, there is limited information regarding the factors influencing supply
chain participants' tendency to adopt and use such technologies.
Furthermore, technologically integrated supply chain systems directly
impact the overall performance of a specific good's production and consumption
process. Martinez et al. (2019) investigated that a blockchain-based supply chain
improves the efficiency process; this system reduces the number of operation
processes, timing, and workload, shows traceability, and enhances visibility to the
different levels of supply chain participants. On the other hand, Kshetri (2018)
investigated the blockchain project at a different level of development in various
areas of supply chain management. The author concluded that a blockchain-based
supply chain affects cost, quality, order placement time, and general public
perception of reliability and minimizes risk while increasing sustainability and
flexibility.
However, historical fishery monitoring and reporting programs have
depended on independent fishery observers, vessel monitoring systems (VMS,
real-time vessel location reporting), landings reports, and self-reported paper
records for a significant portion of fishery-related data collection. For this reason,
fisheries farms introduced electronic technology solutions, i.e., global positioning
systems (GPS), electronic reporting, video cameras, fishing gear sensors, human
observer technologies, etc. Those technology integrations in the fish farms
support other interests, such as business development, monitoring and control,
traceability, and other applications (ICES, 2019). Similarly, technology
integration can bring easy, sustainable, and cost-effective solutions to the fish
marketing system because fish has a relatively short shelf life, and its quality
degrades quickly (Tavares et al., 2021). However, a technology-integrated supply
chain may not yield positive in the fish supply, for example, Lin and Wu (2016)
empirically studied using Taiwan's white shrimp industry and found that a
centralized shrimp supply chain practice does not necessarily bring better yield
compared to the decentralized supply chain.
Like any other sector, fishery sectors have been confronting several
limitations in supply chain networks. Bangladesh's fish and fisheries products
marketing primarily depends on the private sector, and a vast number of
individuals rely on it for their livelihood. It is true that each stage of the marketing
Technological Integration Impact on Fish Supply Chain in Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder
©OIRD 4
channel for fish and fishery products faces various challenges. For example,
Hemal et al.( 2017) concluded, based on fish seed marketing, that lack of cash,
technical competence, high lease value, the high price of production inputs,
violence, fierce market competition, lack of legislative assistance, and other
factors have an impact on stakeholders in this marketing system in the Sylhet
district of Bangladesh. Similarly, Bangladeshi fishermen are unable to effectively
monetize their catch of fish and fisheries products or promote sustainable supply
chain efficiency to bring about substantial change in the fishery industry (Sharif et
al., 2016). Fishers are obliged to sell their catch to local traders because of illegal
power practices. In addition, a variety of prominent factors in the Bangladeshi
fishery industry have created obstacles to employ the available supply chain
network, such as the illegal power practice of Dadon providers (lenders),
insufficient transportation infrastructure, meager catches, high transport costs, and
intermediary pressure (ICE Business Times, 2016; Shafikul et al., 2018;
LightCastle Analytics Wing, 2020, p. 202; Shafiuddin, 2021). Azam et al. (2016)
studied using Bangladesh's data and descriptive illustrations that consumers
obtained only 5% of fish and fishery products directly from fish farms; the other
95% of fish were delivered to consumers through the fish supply chain; however,
there several redundant middleman activities that reduce the financial gain of both
consumers and producers.
In view of the above discussion, some common questions arise. For example,
is there any benefit to technology integration in Bangladesh's fish supply chain?
What are the benefits involved in adopting a technology-integrated supply chain
network available in the fisher sector? Is there any impact of technology
integration on unjustified middleman gain in Bangladesh's fish supply chain? If
the presence of unjustified middleman gain is found in the current fish supply
chain network, how can this challenge be overcome? The main objective of this
study is to find the impact of technology integration in the fish supply chain of
Bangladesh by using data from selected 24 districts and employing the Ordinary
Least Squares (OLS) and a Logistic Regression Approach for empirical
estimation. The empirical study finds that twoG and threeG mobile connections
have mixed impacts on different fish species production in Bangladesh. More
precisely, the twoG mobile connection may positively affect fish production in
Bangladesh because most people adopt twoG mobile phones (Pavel, Burhan, and
Jamee, 2014), but the threeG has an adverse impact.
2.0 Problem Statement
Reportedly, syndicates are very active in Bangladesh's fish supply chain. The fish
market does not function properly because of their presence. Both fish producers
and final consumers face financial loss due to the fact that syndicates create
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artificial shortages of fish supply in order to earn excess profit (Dhaka Post, 2022;
Samakal, 2022; Jugantor, 2023). In most cases, fishermen can not sell their catch
at market price and take their own decisions because of the syndicates' illegal
practices. The syndicates force the fishermen to sell the catch to intermediaries
and traders to the latters' advantage (Prothom Alo, 2020; TBS, 2020; Kaler
Kantho, 2023). This leads to severe exploitation. A study (Hasan, 2021) on
Gaibandha sadar of Bangladesh concluded that the fish producers received only
49.3% of the final price, and the remaining 50.7% was received by different
middleman in the fish supply network. Using Chattogram's sea fish data, Sheikh,
Sen, and Hasan (2018) found that fish distribution took much longer time because
of eight to ten syndicate groups who control the fish market of Chattogram.
Furthermore, Azam et al. (2016) studied conducting Bangladesh's data and
descriptive illustrations that only 5% of fish and fishery products directly came
from the fish farmers, but the other 95% of fish were delivered to consumers
through a supply chain network. They also concluded that some of the
intermediaries' activities in the supply chain seem to be redundant due to adding a
cost to the consumer and a financial loss for the fish farmers. Those redundant
activities of intermediaries of the fish supply chain network create challenges
during excess or less supply of fish in Bangladesh (Shareef et al., 2020).
However, those challenges may be solved by introducing the technology-
integrated fish supply chain in Bangladesh. There are several examples of the
positive impact of technology-integrated supply chain networks, for example, if
technological integration in the supply chain is ensured in the production
processes, it reduces the cost and processing time, ensures traceability, increases
reliability, reduces risk, etc. (Kshetri, 2018; Leng et al., 2018; Zhao et al., 2019;
Martinez et al., 2019; Feng et al., 2020). Besides, traditional fish supply chain
actors face challenges in providing fish on time to consumers due to the problems
mentioned in the previous section. Several studies focused on the role of
technology-integrated supply chain networks in addressing those challenges and
found positive and significant effects on the fish supply chain networks (Zhao et
al., 2019; Martinez et al., 2019; Feng et al., 2020). On the other hand, some
studies came up with different conclusions about the technology-integrated supply
chain. For example, Lin and Wu (2016) empirically studied using Taiwan's white
shrimp industry data and found that a centralized shrimp supply chain practice
may not necessarily bring better yield due to a higher price in the farm-gate of the
decentralized supply chain (small-scale shrimp farmers) than in the centralized
supply chain practiced. So, the impact of a technology-based supply chain on the
fishery industry is not straightforward.
Technological Integration Impact on Fish Supply Chain in Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder
©OIRD 6
3.0 Rationale of the Study
Inland water and marine fishery production in Bangladesh has been growing day
by day. However, the fishery sector faces a variety of challenges. For instance,
fishers and fish farms suffer from problems including the lack of transport, illegal
practices of local traders, and lack of financial access (ICE Business Times, 2016;
Shafikul et al., 2018; LightCastle Analytics Wing, 2020, p. 202; Shafiuddin,
2021), overfishing (Valdimarsson, 2007; Ahmed et al., 2010; NEPAD, 2016),
environmental degradation (Valdimarsson, 2007), post-harvest losses and waste
(Affognon et al., 2015; Chan et al., 2019), etc. However, excess and shortage of
fish supply and time pressure create supply chain complexities and challenges
(Shareef et al., 2020). Most of the national daily newspapers (Dhaka Post, 2022;
Samakal, 2022; Jugantor, 2023; Prothom Alo, 2020; TBS, 2020; Kaler Kantho,
2023) report the fish supply chain challenges, i.e., middleman earn an excess
profit, both consumers and producers face financial loss due to the advantage of
fish syndicate, fish producers can not sell their catching freely, etc. Similarly, only
a few scholarly writings address those inconsistencies, i.e., excess profit, the
obstacle to sell freely, etc., in the supply chain networks (Uddin and Sanda, 2016;
Sheikh, Sen, and Hasan, 2018). Additionally, scholarly writing concluded that
only five percent of fishery products are directly collected from fish farmers, and
the remaining part follows a fish supply chain network; however, the unwanted
middleman activities in the fish supply chain may create a financial loss for both
consumers and producers' level (Azam et al., 2016). This unstructured fish supply
chain practice of having redundant players creates challenges during excess or
less supply of fish in Bangladesh (Shareef et al., 2020).
Unfortunately, regarding the published scholarly writing, there hasn't been
much focus from an academic or institutional viewpoint on the relationship
between technology integration and fish supply chain as well as the complexities
and difficulties of the fish supply chain, particularly the lack of logistics support
when surplus and shortage of fish supply exists. The fishery industry can
overcome those challenges using a technology-based fish supply chain. But,
Bangladesh is lagging behind in integrating technology into the fish supply chain
(Azam et al., 2016). This research gap highlights the need for a more in-depth
examination of the impacts of technology integration on the current fish supply
chain and to make some recommendations based on technology-integrated fish
supply chain in Bangladesh.
4.0 Research Questions
The study intends to address the following particular questions:
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1. How does technological integration impact the fish supply chain in
Bangladesh?
2. How does technology integration affect middleman's gain in Bangladesh's
fish supply chain?
3. How does technology integration affect unjustified middleman gain in
Bangladesh's fish supply chain?
4. How can the unjustified middleman gain be eradicated from Bangladesh's
fish supply chain?
5.0 Objectives
The main objective of this study is to explore the impacts of technological
integration in the fish supply chain of Bangladesh. The specific objectives are.
1. To explore the impacts of technological integration in the supply chain of
the Bangladesh fishery industry.
2. To analyze the effects of technology integration on middleman gain in the
fish supply chain of Bangladesh.
3. To investigate the effects of technology integration on unjustified
middleman gain in the fish supply chain of Bangladesh.
4. To make some recommendations to eradicate the unjustified gain from
Bangladesh's fish supply chain.
6.0 Literature Review
The technology-integrated supply chains are widely employed in the industry and
agricultural sectors. The technology-integrated supply chain has a positive impact
on agricultural production. For example, Saurabh and Dey (2021) explored that
agricultural production can be increased by introducing technology-integrated
supply. Besides, after reviewing 84 scholarly articles published between 2000 and
2007, Kamble et al. (2020) identified several challenges, including a lack of
information accuracy, inadequate management, and insufficient supply chain in
the agri-food supply chain. They also concluded that blockchain, the Internet of
Things, and big data could play an important role in the agri-food industry.
Moreover, a technology-integrated supply chain network has a
fundamental impact on the whole performance of a specific good's production and
distribution process. Saurabh and Dey (2021) observed that agricultural
production and quality management could be improved by employing the
blockchain, the Internet of Things, wireless sensor networks, cloud computing,
and machine learning technologies. Kshetri (2018) explored blockchain
technology implications in the different levels of supply chain networks and
concluded that a blockchain-based supply chain reduces risk while enhancing
Technological Integration Impact on Fish Supply Chain in Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder
©OIRD 8
sustainability, flexibility, cost, quality, order placement time, and the general
public's perception of reliability.
According to Islam and Habib (2013), the production of fish can be boosted
through the maximum use of the already available domestic resources using
contemporary and scientific methods of fish culture and fishing techniques. In
recent decades, the technology-integrated supply chain has played a fundamental
role in the fishery. Several studies show that a technology-integrated supply chain
reduces the cost and processing time, offers traceability, minimizes general
people's stigma and increases reliability, reduces risk, etc. (Kshetri, 2018; Leng et
al., 2018; Zhao et al., 2019; Martinez et al., 2019; Feng et al., 2020).
However, the fishery industry faces a significant number of challenges
based on socioeconomic structure. Hasselberg et al. (2020) reported several
challenges that fishing farms commonly face in supply chain networks in Ghana.
They found that millions of Ghanaians depend on fisheries for their livelihood and
access to nutrient-dense small fish species, which is fundamentally related to
small-scale fisheries rather than the industrial or aquaculture sectors, while fish
availability is a growing concern for the small-scale fishers. The authors also
reported that, endangering the availability of fish and the sustainability of fish
stocks, the entry of foreign industrial trawlers also causes a decline in the incomes
of already vulnerable small-scale fishers, processors, and traders. Racioppo et al.
(2021) explored the global challenges of fish sustainability for the fishery industry
due to overfishing, which led to the reduction of stock worldwide. They also
mentioned several factors, i.e., nitrogen compounds, lipids, minerals and
pigments, and fish-based chitosan, that are responsible for reducing global fish
stock. Another study shows that worldwide freshwater fish are constantly in
danger due to overfishing, pollution, habitat loss, damming, foreign invading
species, and climate change (Reid et al., 2013). Furthermore, Ghose (2014)
identified several natural and man-made challenges, including climate change,
natural disasters, uneven urban and industrial development, overfishing, and
environmental pollution, which pose difficulties for the fisheries industry of
Bangladesh. Similarly, Paul and Vogl (2011) found that there are two major
impacts such as socioeconomic (market unrest, livelihood displacement, market
fluctuations) and environmental (mangrove degradation, salt water, pollution,
diseases, inappropriate management practice, etc.) challenges to the shrimp fish
farming of Bangladesh. Additionally, some research shows that fish producers are
obliged to sell their fish to local traders because of unlawful local power practices,
Dadon (illegal financing), lack of transport facilities, small catching, high cost of
transport, mediators' illegal pressure, etc. (ICE Business Times, 2016; Shafikul et
al., 2018; LightCastle Analytics Wing, 2020; Shafiuddin, 2021). Similarly,
Journal of One Initiative Research and Development ISSN: 2958-2776
Vol.: 03 Issue: 01 January-June 2024
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Kamble et al. (2020) identified several challenges, i.e., the lack of
industrialization, inadequacy of management, information accuracy, and
insufficient supply chain are significant issues in the agri-food supply chain by
reviewing 84 scholarly articles from 2000 to 2017. They also mention the
importance of the Internet of Things, blockchain, and big data technologies in the
agricultural supply chain network and propose a technology-integrated supply
chain model. Likewise, a number of scholarly studies identified some common
challenges, i.e., Overfishing (Valdimarsson, 2007; Ahmed et al., 2010; NEPAD,
2016) and environmental degradation (Valdimarsson, 2007), Fish post-harvest
losses and waste (Affognon et al., 2015; Chan et al., 2019) in the fishery industry.
The challenges of the fishery sector can be overcome by using the technology-
integrated supply chain while ensuring the socioeconomic conditions. Several
studies show that technology-integrated supply reduces the cost and processing
time, offers traceability, minimizes general people's stigma and increases
reliability, reduces risk, etc. (Kshetri, 2018; Leng et al., 2018; Zhao et al., 2019;
Martinez et al., 2019; Feng et al., 2020). According to the survey using
Bangladesh's data and descriptive illustrations, only 5% of fish and fishery
products came directly from fish farmers, and the remaining 95% of fish were
delivered to consumers through the fish supply chain network, but several
unwanted activities of middleman increase the cost and reduce the financial gain
of consumers and producers level (Azam et al., 2016). Those redundant
middleman activities in fish supply create unjustified gains for middleman that
can be eradicated by introducing a centralized technology-integrated supply chain
network in Bangladesh.
However, the acceptance of a centralized supply chain network in the fishery
industry is not straightforward. For instance, Lin and Wu (2016) empirically
studied using Taiwan's white shrimp industry and found that a centralized shrimp
supply chain practice does not necessarily bring better yield. On the other hand,
many researchers found that technology-based supply chain practice positively
impacts the agro-based industry, including the fishery sector (Kshetri, 2018; Leng
et al., 2018; Zhao et al., 2019; Martinez et al., 2019; Feng et al., 2020).
In terms of the above discussion, only a few studies concentrated on the
impact of technology integration in the fish supply chain—for instance, some
focus on global and Bangladesh's fish trading challenges using simple graphical
and tabular presentations. In addition, the relationship of technology integration
with the fish supply chain, middleman gain, and unjustified middleman gain is
still inconclusive. A gap in the existing literature is thus apparent. This research
intends to reduce the gap.
Technological Integration Impact on Fish Supply Chain in Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder
©OIRD 10
7.0 Theoretical Framework
The technology-integrated supply reduces the cost and processing time. It offers
traceability, minimizes general people's stigma, increases reliability, and reduces
risk. Several scholarly writings (Kshetri, 2018; Leng et al., 2018; Zhao et al.,
2019; Martinez et al., 2019; Feng et al., 2020) use blockchain-based solutions to
address the food traceability difficulties, benefits of blockchain technology, and
obstacles to implementing blockchain-based traceability systems implementation,
where they found that blockchain-based solution enhances food traceability
systems based on blockchain technology. On the other hand, the technology-
integrated fish supply may negatively impact Taiwan's shrimp fishery industry.
Moreover, they found a higher price in the decentralized supply chain practiced at
farms’-gate (small-scale shrimp farmers) than in the centralized supply chain
practiced by relatively large fishing farms (Lin and Wu, 2016). So, the
technology-based fish supply chain affects the fishery industry because it may not
match the socioeconomic condition.
Several scholarly articles examined the technology integration into the
agricultural industry, i.e., artificial intelligence in agricultural farming ( Kumar et
al., 2016; Omid et al., 2013; Pang et al., 2015; Wehberg et al., 2017; Kittipanya-
ngam and Tan, 2020). Some studies focused on the Internet of Things applied for
monitoring weather, animal health and condition, and self-learning prediction on
food production and processing (Kumar et al., 2016; Pang et al., 2015; RuizGarcia
et al., 2009; Wehberg et al., 2017; Kittipanya-ngam and Tan, 2020). Furthermore,
blockchain technology is used for maintaining digital tracking and storage of all
stages of the information supply chain (Koonce, 2017; Lewis, 2017; Wehberg et
al., 2017; Kittipanya-ngam and Tan, 2020). Besides, only a few articles focused
on the technology-integrated fish supply model, for example, cloud computing
applied for the traceability system of fish and fishery products in the fish supply
chain network (Moga, 2017), Blockchain-based fish supply chain in the Thai fish
industry (Tsolakis et al., 2021), etc. Most of the technology-integrated supply
chains are introduced in developed countries. Sengupta et al. (2021) designed
satellite imagery and blockchain technologies in the fish supply chain in India.
They emphasize how such technologies help poor fishers in developing countries
to have more options to earn by improving the supply chain's resilience.
8.0 Methodology
8.1 Data and Variables
This research has collected secondary cross-sectional data as of January 2023
from four different entities, i.e., the Department of Fisheries, the Department of
Agricultural Marketing, BBS (Bangladesh Bureau of Statistics), and BTRC
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(Bangladesh Telecommunication Regulatory Commission). The variables under
consideration include cell phone use, internet access, farm-level production cost
and selling price of fish, wholesale price, retail price, agricultural loan
disbursement, etc. During the estimation process of this study, cell phone use and
mobile internet access represent technological integration in the fish supply chain.
Table 1: list of variables
No. Variable Description Source
1. lnrui_production
Natural log of Rui fish production
in different districts of Bangladesh
The department of
fisheries of Bangladesh
2. lntwoG
Natural log of Two G mobile
phone connection in different
districts of Bangladesh
Bangladesh
Telecommunication
Regulatory Commission
(BTRC)
3. lnthreeG
Natural log of Three G mobile
phone connection in different
districts of Bangladesh
Bangladesh
Telecommunication
Regulatory Commission
(BTRC)
3. lnloan
Natural log of agricultural loan
disbursement in different districts
of Bangladesh
Bangladesh Bureau of
Statistics (BBS)
4.
lnfarm_level_selli
ng_price
Natural log of farm level selling
price of Rui fish produced in
different districts of Bangladesh.
The Department of
Agricultural Marketing
of Bangladesh
5.
lnretail_selling_p
rice
Natural log of the retail selling
price of Rui fish produced in
different districts of Bangladesh.
The Department of
Agricultural Marketing
of Bangladesh
6.
lnmiddleman_gai
n
Natural log of total middleman
gain from Rui fish trading. This is
calculated by subtracting the farm-
level price from the wholesale
price of Rui fish in different
districts of Bangladesh.
The Department of
Agricultural Marketing
of Bangladesh and the
author's calculation
7.
Unjustified_gain_
dummy
The wholesaler can make a
maximum profit of 15% according to
the Agricultural Marketing Rules
2021. The value of 1 to indicate the
presence of unjustified middleman
gain, and 0 to indicate the absence of
it based on the profit margin of 15%.
The Department of
Agricultural Marketing
of Bangladesh and the
author's calculation
Technological Integration Impact on Fish Supply Chain in Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder
©OIRD 12
8.2 Descriptive Statistics
This research has conducted descriptive statistics, i.e., mean, median, and
correlation matrix. Those descriptive analyses are employed depending on the
secondary cross-sectional data.
8.3 Econometric Estimation
This study applied the Ordinary Least Squares (Gauss, 1809) and Logistic
Regression(Cox, 1958) Approach to estimate the issues of this study's objectives
using secondary data of fish species from 24 different districts of Bangladesh. The
OLS and Logistic Regression estimation processes are explained below:
According to the Agricultural Marketing Rules 2021
1
, for producers,
wholesalers, and retailers in the fish supply chain, maximum acceptable profit
margins are 30%, 15%, and 25% at each stage, respectively. Any violation of
these limits indicates the presence of unjustified gain. Keeping this in mind and
considering my focus on middleman (wholesalers); a dummy variable ( ) is
constructed for wholesalers as follows.
In other words, the dummy variable, namely 'unjustified gain dummy',
assumes the value of 1 to indicate presence of unjustified middleman gain and 0
to indicate absence of it.
First of all, the use of cell phones and internet access represents technological
integration, the key independent variable. Besides, there are three dependent
variables, i.e., fish production, middleman gain, and unjustified gain. This study
would like to estimate the impact of technology integration on fish production by
using the OLS estimation approach as follows:
The dependent variable, , refers to the Rui production, and the independent
variable, refers to the Two-G mobile phone connection and
indicates the three-G mobile connection, is the agricultural loan
disbursement, refers to the farm-level price of Rui fish and is
1
To establish maximum profit margins for agricultural products at the production, wholesale, and
retail levels, the government of Bangladesh has introduced the Agricultural Marketing Rules 2021.
According to the Agricultural Marketing Rules, the maximum reasonable profits are 30% for the
farms' production level, 15% at the wholesale stage, and 25% at the retail level for fresh, dried,
salted, and frozen fish.
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the amount of middleman gain received by trading Rui fish. The variable ni
indicates the error term, and i represents the districts.
The dependent variable,Mi , refers to the amount of middleman gain from Rui
fish production, and the independent variable, refers to the Two-G mobile
phone connection and indicates the three-G mobile connection, is
the agricultural loan disbursement, indicates the Rui fish production,
refers to the retail selling price and refers to the farm-level price of Rui
fish. The variable indicates the error term, and represents the districts.
Additionally, this study has estimated how technological integration impacts
the unjustified middleman gain. However, the dependent variable is indeed a
dummy variable. So, this research can apply the Linear Probability Model (LPM)
due to the regressand is binary, and the LPM model follows the Bernoulli
probability distribution with that 1(presence of unjustified
middleman gain) and that
. Unfortunately, LPM
violates several assumptions (heteroscedastic variance and non-normality of error
term) of classical linear regression (Chatla and Shmueli, 2016). Additionally, if
this study applies the LPM model, there is no guarantee that the estimated
fulfill the probability restriction ( ; if the estimated value of is less
than or greater than . This problem can be solved using the Logistic estimation
approach as follows.
To empirically estimate the impacts of technology integration on unjustified
middleman gain, indicates the dependent variable (dummy); the presence or
absence of unjustified middleman gain in each species. represents the odd
ratio, where , if the unjustified middleman gain exists and , if there is
no unjustified middleman gain. More specifically, it shows the rate of change in
probability with respect to change in independent variables. The independent
variable, refers to the twoG mobile phone connection and
indicates the three-G mobile connection, is the agricultural loan
disbursement, indicates the Rui fish production, refers to the retail
Technological Integration Impact on Fish Supply Chain in Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder
©OIRD 14
selling price and refers to the farm-level price of Rui fish. The variable
indicates the error term, and represents the districts.
This research has used Microsoft Excel for data mining purposes. In addition,
STATA and SPSS have been used to calculate qualitative and quantitative
estimates.
9.0 Result and Discussion
9.1 Descriptive Statistics
For the estimation purpose, this study gathered data on farm level price of Rui
fish, retail price, agricultural loan disbursement, and the number of towG and
threeG connected cell phones from 24 districts of Bangladesh. The main purpose
of this study is to explore the impact of technological integration on fish
production. Table 2 reperesents the descriptive statistics of dependent and
independent variables. Table 3 shows the correlation matrix.
Table 2: Descriptive Statistics
Variable Obs Mean Std. Dev. Min Max
lnrui_production 24 8.234 1.207 5.403 10.005
Lnmiddleman_gain 24 3.355 0.422 2.708 4.094
Unjustified gain dummy 24 0.417 0.504 0.000 1.000
lntwoG 24 14.717 0.695 13.345 16.235
lnthreeG 24 14.188 0.781 12.719 15.852
Lnloan 24 11.789 0.591 10.180 12.858
Lnfarm level price 24 5.375 0.111 5.136 5.617
lnretail_selling price 24 5.613 0.110 5.416 5.829
Source: Author's Estimation
The correlation matrix, table 3, indicates that almost all variables are positively
associated except the retail price and farm level price of Rui fish with the Rui fish
production. The twoG and threeG variables are negatively associated with
middleman gain and unjustified gain, respectively. The firm-level price is
inversely related to middleman gain, unjustified gain, twoG, threeG, and
agricultural loan disbursement. The retail selling price is positively related to
middleman gain and unjustified gain but negatively related to twoG and threeG
mobile connection.
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9.2 Econometric Analysis
This study uses the OLS and Logistic Regression models for econometric
analysis. The OLS estimation approach is applied for estimating the relationship
between fish production and the key variables of technological integration (twoG
and threeG mobile networks users) and other control variables, i.e., agricultural
loan disbursements, wholesale, retail and grower price of fish, and unjustified
gain using the twenty-four districts' data of rui fish. Additionally, this study
applied the OLS estimation model to analyze the impact of technological
integration (twoG and threeG mobile network) on unjustified gain along with
other control variables, such as agricultural loan disbursements, fish production,
and retail and grower price of fish. Besides, the Logistic Regression model has
been conducted for the estimating the technological integration's (twoG and
threeG mobile networks users) impact on unjustified gain (dummy variable) with
the other control variables, such as fish production, agricultural loan
disbursements, retail and grower price of fish. The estimated results have given
mixed results: the impact of technological integration in fish production and
unjustified gain from fish trading. Though the estimated results have mixed
results, it may give a policy indication for fish growers, traders, policymakers, and
government authorities.
9.2.1 Technological Impact on Rui Fish Production
In the estimated result (Table 4) based on equation 2, the technological integration
variables have mixed results, i.e., twoG mobile connection may increase and the
threeG mobile connection may reduce the Rui fish production, but the estimated
result is statistically insignificant.
Technological Integration Impact on Fish Supply Chain in Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder
©OIRD 16
Table 4: OLS Estimation
Linear regression
Number of obs =24
F(5, 18) = 10.5
Prob > F = 0
R-squared = 0.6209
Root MSE = 0.8403
lnrui_production Coef. T [95% conf. Interval]
lntwoG 0.995 0.510 -3.093 5.084
(1.946)
lnthreeG -0.700 -0.410 -4.257 2.857
(1.693)
Lnloan 1.362*** 4.650 0.747 1.977
(0.293)
lnfarm_level_selling_price 1.264 0.840 -1.899 4.428
(1.506)
lnmiddleman_gain -0.031 -0.840 -0.109 0.046
(0.037)
_cons -18.886* -1.760 -41.442 3.671
(10.736)
*=<10%. **=<5%, ***=<1% level of significance
Source: Author's Estimation
The twoG mobile connection's findings comply with the study in Indonesian - fish
production increases due to the technologically integrated supply chain, but the
threeG mobile connection does not support the previous finding in Indonesia
(Dwi Ardianto and Mudjahidin, 2022). Agricultural loan disbursement and Rui
fish price at the farm level may increase Rui fish production, and the estimated
coefficient of agricultural loan disbursement is statistically significant. Financial
support for fish farming increases the productivity, sales, and profitability of fish
farms in in Nigeria(Oparinde, Amos, and Adeseluka, 2017; Akerele et al., 2019).
A similar result is found in a study of Bangladesh, e.g., agricultural loan
disbursements positively impact fish production (Sarker, 2016). Besides,
middleman's gain from Rui fish trading may reduce Rui fish production, while the
estimated findings are statistically significant. This means that the higher
middleman gains from Rui fish trading may lead to reduced production of Rui
fish.
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9.2.2 Technological Integration Impact on Middleman Gain from Rui
FishTrading
Table 5: OLS Estimation
Linear Regression
Number of obs = 24
F(6, 17) = 8.16
Prob > F = 0
R-squared = 0.526
Root MSE =0.3377
lnmiddleman_gain Coef. T [95% Conf. Interval]
lntwoG 0.059 0.080 -1.597 1.716
(0.785)
lnthreeG -0.171 -0.250 -1.599 1.257
(0.677)
Lnloan 0.162 0.800 -0.268 0.593
(0.204)
lnrui_production -0.123 -1.140 -0.349 0.104
(0.107)
lnretail_selling_price 3.816*** 4.510 2.031 5.601
(0.846)
lnfarm_level_selling_price -3.463*** -3.170 -5.766 -1.160
(1.091)
_cons 1.195 0.290 -7.567 9.956
(4.153)
*=<10%. **=<5%, ***=<1% level of significance
Source: Author's Estimation
In the estimated result (Table 5) based on equation 3, the technological
integration variables, i.e., twoG and threeG mobile connections, may positively
impact the middleman gain from rui fish production, where the twoG mobile
connection is statistically insignificant. Rui fish production and farm level price
may have a negative impact on the middleman gain from fish trading, the
estimated result of farm level price is statistically significant. Besides, agricultural
loan disbursement and the retail price may positively affect the middleman gain
from rui fish, where the estimated result of the retail price is statistically
significant at a 5% level.
Technological Integration Impact on Fish Supply Chain in Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder
©OIRD 18
9.2.3 Technological Integration Impact on Presence of Unjustified Gain in
Rui Fish Trading
Table 6: Logistic Regression
Logistic Regression
Number of obs = 24
Wald chi2(6) = 12.44
Prob > chi2 = 0.0293
Log pseudolikelihood = -12.8191
Pseudo R
2
= 0.2136
unjustified_gain_dummy Coef. Z [95% Conf. Interval]
lntwoG 1.012 0.190 -9.540 11.563
(5.383)
lnthreeG -2.124 -0.470 -10.931 6.683
(4.493)
Lnloan 0.455 0.240 -3.281 4.191
(1.906)
lnrui_production -0.717 -1.070 -2.035 0.602
(0.673)
lnretail_selling_price 16.670* 1.640 -3.227 36.567
(10.152)
lnfarm_level_selling_price -20.450* -1.650 -44.729 3.828
(12.387)
_cons 31.720 0.610 -69.392 132.833
(51.589)
*=<10%. **=<5%, ***=<1% level of significance
Source: Author's Estimation
This study (table 6), based on equation 4, shows the impact of
technological integration on the presence of unjustified gain from rui fish
production(dummy variable) using the Logistic Regression estimation method.
The twoG may positively and threeG may adversely affect the presence of
unjustified gain from rui fish production, but both estimated results are
statistically insignificant. Rui fish production and retail selling price may increase
the presence of unjustified gain from rui fish, and the estimated result of retail
selling price is statistically significant at 10% level. However, other control
variables, i.e., Rui fish production and farm-level selling price, may reduce the
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©OIRD 19
presence of unjustified gain from Rui fish, and the estimated result of farm-level
selling price is statistically significant at 10%.
10.0 Recommendation
The empirical study concluded that technological integration may positively
impact the fish supply chain in Bangladesh. According to quantitative analysis,
this study suggests some necessary recommendations based on econometric
estimations.
i. Invest in robust digital infrastructure to ensure reliable internet
connectivity and access to technological tools across all regions,
particularly in rural and remote areas.
ii. Implement extensive training programs to equip fish farmers, processors,
and supply chain workers with the necessary skills to use and benefit from
technological innovations effectively.
iii. Government subsidies and incentive programs can help offset the initial
costs of investing in technology for fish farmers.
iv. Collaborative partnerships between government agencies, research
institutions, non-profit organizations, and private sector stakeholders can
drive innovation and knowledge sharing in the fish farming sector.
v. Develop policies and initiatives that ensure equitable access to technology
for small-scale and marginalized fish farmers, reducing the digital divide
and fostering inclusive growth.
vi. Encourage research and development in sustainable inland fish farming
practices and innovative technologies tailored to the specific needs of the
Bangladeshi fish supply chain.
vii. Establish mechanisms for continuous monitoring and evaluation of
technology integration initiatives to assess their impact and make
necessary adjustments.
By implementing these recommendations, Bangladesh can build on the progress
achieved through technology integration, ensuring a resilient, competitive, and
sustainable fish supply chain that benefits all stakeholders involved.
11.0 Conclusion
According to the empirical estimation, the integration of technology may have a
significant positive impact on the fish supply in Bangladesh. Additionally,
technology integration may reduce the middleman-gain and presence of
unjustified gain in Bangladesh's fish supply chain. Through the adoption of
modern technological tools and systems, the fish supply chain has seen
improvements in efficiency, traceability, and sustainability. Finally, this research
Technological Integration Impact on Fish Supply Chain in Bangladesh: An Empirical Analysis
Shahidur Rahaman Mazumder
©OIRD 20
will fill the literature gap and bring new insights into government fishery policies,
fish traders, fish farmers, and consumers.
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