1 INTRODUCTION

Green logistics (GL) refers to investing in

internationally standardized green technology in

logistics activities with the aim of reaching sustainable

development goals especially those that concern the

environment and human health [1,2]. Prior studies

have highlighted some effective outcomes from

applying green approaches to the logistics operational

activities including gaining economic advantages and

a competitive edge, by focusing on the strategy of

managing the distribution movement of all the

material along the chain, product inventory

management, operational activities within the

relevant facilities, social responsibility, and packaging

treatment, all to lower the environmental impacts [3-

5]. Nowadays, GL has gained great attention since the

negative impacts of the maritime freight transport

industry became increasingly prominent through

pollution in the surrounding sea and inland

environment and human health degradation [6-8]. In

Taiwan, the maritime freight transport industry has

shown a drastic transformation in recent years due to

the fluctuating global conditions and recently

experienced an increasing demand for the container

shipping market influenced by the global economic

activity leading to an increase in adverse effects on the

environment [9-11]. As an effect, the industry has

contributed to lowering air quality, especially in cities

where ports are located through airborne pollutants at

an endangering level that harm both the environment

and human health; some of the causes include a

substandard choice of fuels and conventional use of

energy from facilities to ships while berthing [12]. In

addition to airborne pollution, due to improper

control and monitoring, Taiwan also suffers from

marine pollution with solid material waste from

freight transport [13]. Thus, this study argues that GL

Multicriteria Assessment of Green Logistics in Taiwan’s

Maritime Freight Transport: Green Packaging and

Green Transportation as Driving Aspects

R.Y. Sujanto, S.L. Kao & M.F. Yang

National Taiwan Ocean University, Keelung City, Taiwan

ABSTRACT: This study aims to establish a multicriteria-based model for understanding green logistics in

Taiwan's maritime freight transport industry. Prior studies have emphasized certain successful results from

using green measures on the operational logistics operations, including establishing a competitive advantage

and economic benefits. However, the literature tends to be inadequate and fragmented when discussing how

green logistics relate to environmental sustainability. This study proposes a framework containing 5 aspects and

35 criteria. The fuzzy Delphi and best-worst methods are adopted to evaluate the validity and reliability. A

decision-making trial and evaluation laboratory method is used to examine how the attributes’

interrelationships. The results reveal that green packaging and green transportation become the determining

aspects to enhance green logistics. The top five criteria to prioritize is presented including product life cycle

impact, green packaging material, use of energy at facilities, intermodal transport, emissions of transporting

vehicles within the area of facilities.

http://www.transnav.eu

the

International Journal

on Marine Navigation

and Safety of Sea Transportation

Volume 18

Number 1

March 2024

DOI: 10.12716/1001.18.01.

offers a potent effect to eliminate the impacts that are

caused by maritime freight transport activities in

Taiwan.

It is crucial to successfully balance social,

environmental, and economic goals throughout all

logistics activities, including transportation, storing,

packaging, discharging, and processing, as the

environmental externalities of logistics operations—

which are mostly associated with greenhouse gas

emissions, noise, and accidents—are something that

GL seeks to minimize [14-16]. A collection of

interconnected operations is embodied involving

inventory management and freight transportation,

material and packaging handling, maintenance of

facilities, and internal organization social

enhancement, all of which are necessary to move

items through an effective supply chain process

[17,18]. Although the literature has addressed GL and

its implications on those operations, shortcomings

remain found [14,17,19]. For instance, Trivellas et al.

[20] argued that despite the extensive literature on

GL, studies on its relation to sustainability

performance tend to be fragmented and incomplete.

Nevertheless, the shortcomings are mostly

concentrated on finding the determining attributes

that foster GL development.

For instance, there have been inconsistent findings

regarding the attribute significance of green social

performance, packaging, inventories, facilities, and

transportation in affecting GL [15,21,22]. In particular,

on one hand, Trivellas et al. [20] claimed that green

packaging is a significant GL initiative for reducing

the environmental impact and improving operational

efficiency; however, on the other hand, other studies

claimed that it is the green transportation that

becomes the causal aspect due to the apparent

emissions to the environment [3,5,14]. In addition,

different other studies have highlighted that, among

the significant attributes, green social performance

plays a notable role in ensuring GL adoption and

development acceleration in managing environmental

risks [19]. Yet, Liu & Ma [16] argued green facilities

are the determining attribute that potentially

accelerates GL. Thus, these inconsistencies in

understanding the crucial attributes of developing GL

indicate a call for further investigation.

In practice, GL in the maritime freight transport

industry seeks to minimize the environmental

hazards and social concerns due to the flows of

logistics and maritime operations of vessels in

navigation and visiting the port [5,23]. For example,

from the operational perspective, the emissions of

transport units near the facilities such as ships stem

from the engines that are kept on while moored, from

the use of energy powered from onshore facilities, and

heavy fuel oil (HFO) used by ship engines containing

high sulfur [14,24,25]. According to Svindland [25],

the current average use of HFO is 2.7% which is lower

than the global sulfur cap of 3.5%, even though the

limits have been restricted to 0.1% for ships that enter

Emissions Control Areas. From the social perspective,

Agyabeng-Mensah et al. [19] argued that there needs

an improvement of an organization’s reputation via

the adoption of measures that protect society and the

welfare of employees while meeting environmental

standards. Moreover, the social perspective concerns

issues about health and safety, training and education

to improve skills, equal opportunities policy, child

labor, and forced labor. However, these studies were

conducted separately and thus showed mixed results

causing inconsistent and segmented conclusions.

Further, the interactions among the GL attributes and

their influence on improving the GL performance are

underexplored. Thus, this study incorporates multiple

criteria to determine the drivers in developing GL for

the maritime freight transport industry.

Prior studies have examined the attributes to

construct and improve GL using both qualitative and

quantitative methods [22,26,27]. Yet, there is a missing

understanding in confirming the main GL driving

attributes, exploring the causal interrelationship

among the aspects and criteria, and identifying the

significant ones. A hybrid method is applied to

address the shortcoming, involving the fuzzy Delphi

method (FDM), fuzzy decision-making trial and

evaluation laboratory (FDEMATEL), and best-worst

method (BWM). FDM is effective to select and

validate the important criteria using the linguistic

preferences of the panel of experts [28]. FDEMATEL is

exploited to understand the driving aspects and

criteria while identifying the causal interrelationships

[29]. BWM is adopted to check the attributes’

consistency to confirm the reliability based on a

pairwise comparison [30]. The following are the

study's objectives.

− To use qualitative information to create a valid set

of GL attributes

− To investigate the causal-effect interrelationships

between the GL attributes under uncertainty

− To determine the most important criteria for

enhancing GL in the maritime freight transport

industry.

The following contributions are separated to the

theory and to the industry: (1) confirming a valid set

of GL attributes, (2) identifying the GL attributes

causal interrelationships, and (3) giving practitioners

of maritime freight transport useful and practical.

2 LITERATURE REVIEW

This part presents the theoretical arguments and

attributes of GL based on the proposed framework,

GL in maritime freight transport, proposed measures,

and the proposed method.

2.1 Theoretical background

2.1.1 Green logistics

GL is defined as the process of transportation,

storage, and distribution which seeks to fulfill

consumer demand while reducing the environmental

impacts and optimizing product profitability from the

source to the point of consumption [31]. GL involves

greening the logistical functions including

transportation, supporting facilities, inventories,

packaging, and social performance [4,15,22].

According to Agyabeng-Mensah et al. [19], GL

supposedly exchanges information with those

involved in transporting commodities around the

supply chain. According to Mohsin et al. [31], the

important goal of GL is to conserve the environment

by reducing the detrimental consequences that

logistics operations have, all while successfully

reducing environmental destruction and operation

costs and enhancing the competitiveness of the goods

and services. Liu & Ma [16] asserted that in addition

to environmental problems, a lack of GL adoption

might result in high logistical costs, which would

raise the overall societal costs of economic growth and

provide risks to human health owing to a polluted

environment. There are a few benefits that have been

found that might help GL possibly minimize

environmental harm and operating expenses while

increasing energy savings and freight and service

competitiveness through decreased carbon emissions

and waste [31,32].

Yet, despite the potential advantages of GL in

reducing the environmental impact and logistics costs,

the literature has identified some shortcomings in

investigating GL. For instance, Trivellas et al. [20]

argued that there is a complexity in understanding GL

because the logistics functions are interdependent

making it challenging to measure the sustainability in

all the areas. de Souza et al. [18] criticized that GL

tends to have an overlapping definition with reverse

logistics and that the two should be separated by the

activities; for example, while reverse logistics includes

recycling, remanufacturing, and reusing packaging,

GL should be focused on packaging reduction,

emissions, and impact minimization. Moreover, prior

studies highlighted that GL is understudied in

understanding its role in sustainable development

and underexplored in the context of transportation

facilitation [33]. Therefore, to understand the

attributes that build an effective GL model, this study

incorporates the relevant logistics activities including

green social performance, green packaging, green

inventories, green facilities, and green transportation.

2.1.2 Theoretical structure and measures

In measuring and understanding GL, this study

incorporates the theoretical aspects of green social

performance, green packaging, green inventories,

green facilities, and green transportation. Each aspect

contains a number of criteria that describe the aspect

and measure GL from the industrial point of view.

Figure 1. Proposed framework of green logistics measures

3 MATERIALS AND METHODS

This section presents the GL in maritime freight

transport, the industrial background of maritime

freight transport in Taiwan, and the application of

methods including FDM, BWM, and FDEMATEL.

3.1 Green logistics in maritime freight transport

GL in maritime freight transport has been understood

as environment-oriented logistics activities that are

outlined with maritime transportation, logistics, and

supply chain management consisting of transporting

freight or cargo between two ports by waters [7,11,34].

In addition to its orientation to the environment,

studies have suggested that advances and investment

in green technology in the freight transport logistics

systems bring certain competitive advantages of

international trade globally such as efficiency in the

transportation and distribution systems and long-

term cost savings [2,35]. However, some GL studies in

maritime freight transport often neglect the external

costs in both reducing the transportation costs such as

freight value and inventory cost, and boosting

profitability, economic productivity, and efficiency

[1,36,37]. For instance, Facchini et al. [38] argued that

there are many factors that affect the logistics

efficiency in freight transport such as congestion of

berth, unreliable vessel schedule, and lack of docks at

some marine terminals. This study suggests that the

adoption of GL in maritime freight transport

inherently eliminates those hindering factors.

Moreover, Agyabeng-Mensah et al. [19] emphasized a

lack of industry range in GL where the existing

studies are focused on manufacturing enterprises

creating a limit in generalizing the conclusions and

ignoring other industries that contribute considerably

to environmental pollution.

3.2 Data collection

Experts’ linguistic preferences are assessed based on

the critical GL attributes using the FDM, BWM, and

FDEMATEL. After combing the literature of prior

studies for proposing the initial GL attribute set of

aspects and criteria, to communicate the information

and expert system dependability, both online and in-

person interviews are carried out. Questionnaires are

prepared and provided to collect the experts’

linguistic preferences. Using a purposive sample

approach, a panel of 17 experts is selected based on

their high level of expertise, familiarity with GL and

maritime freight transport, and position within the

firm. The panel involves 12 practitioners and 5

academics and researchers. Appendix B presents the

experts’ details.

3.3 Fuzzy Delphi method

The classic Delphi and fuzzy theory approaches have

been merged to create the fuzzy theory- Delphi

method (FDM), which aims to resolve ambiguity in

the experts' consensus while expediting the inquiry

[28,29,39]. FDM is used because of its ability to handle

the fuzziness of expert assessments, which enhances

the effectiveness and quality of the questionnaire [40].

Table 1. Transformation of linguistic terms

________________________________________________

Linguistic terms based on Corresponding TFNs

importance level

________________________________________________

Extreme (0.75, 1.0, 1.0)

Demonstrated (0.5, 0.75, 1.0)

Strong (0.25, 0.5, 0.75)

Moderate (0, 0.25, 0.5)

Equal (0, 0, 0.25)

________________________________________________

3.4 Best-worst method

The best and worst criteria for each aspect are

compared pairwise with the other criteria using the

BWM, a multi-criteria decision-making approach, to

determine weights [30]. The method weighs the

criteria to identify the best and worst.

3.5 Fuzzy decision-making trial and evaluation laboratory

FDEMATEL combines fuzzy set theory and the

conventional DEMATEL method. The combined

approach works well to identify connections between

the attributes and order them according to how much

of an impact they have on one another, both causally

and effectually [41]. The fuzzy set theory works well

for converting the linguistic preferences into crisp

values when using this approach since the anticipated

responses depend on the expertise and experiences of

the expert panel in the form of linguistic preferences,

as demonstrated in Table 2.

Table 2. Corresponding triangular fuzzy numbers' linguistic

preferences

________________________________________________

Linguistic preferences based on Corresponding TFN

influence level

________________________________________________

Very high influence (VHI) (0.75, 1.0, 1.0)

High influence (HI) (0.5, 0.75, 1.0)

Medium influence (M) (0.25, 0.5, 0.75)

Low influence (LI) (0, 0.25, 0.5)

Very low influence (VLI) (0, 0, 0.25)

________________________________________________

3.6 Proposed analytical steps

This study proposes analytical steps, as follows.

1. Based on a review of the past literature, the initial

GL attribute set of attributes and criteria is

presented.

2. For validity, a questionnaire is used to collect the

experts’ preferences using FDM for confirming

and validating the GL hierarchical structure.

3. For reliability, BWM is employed to check the

reliability of the aspects and criteria that measure

GL. Using the highest and lowest weights of each

element, the FDM findings are used to determine

the best and worst criteria.

4. For cause and effect interrelationships, the

FDEMATEL is used to discover the crucial

requirements for creating GL practices in Taiwan's

marine freight transport as well as to identify the

hierarchical structure’s causal interrelationships.

The crisp values are calculated and arranged into

initial direct relations. Then, a map is created to

visualize the cause-and-effect diagram of the

aspects and criteria.

4 RESULTS

This part of the study uses the FDM to show the

characteristics' validity, verifies their reliability using

the BWM, and looks at how the attributes relate to

causes and effects using the FDEMATEL approach.

4.1 Validity of measures

The initial proposed set of attributes includes five

aspects containing 35 criteria as presented in

Appendix A. Validation of the attributes based on the

experts’ assessments is conducted by removing the

less important criteria, resulting in a success in

producing valid four aspects and 17 criteria. The

method refined the valid attributes which results in

the threshold of γ = 0.6277. Table 3 shows the valid

attributes along with the passing weights and

presents the renamed and reordered aspects and

criteria after the elimination process. Thus, as a result,

after the evaluation process, the remaining valid

aspects include green inventories (A1), green facilities

(A2), green packaging (A3), and green transportation

(A4).

Table 3. Validated green logistics attributes

________________________________________________

Aspects Initial Renamed Criteria Weights

code code

________________________________________________

A1 Green C1 C1 Product life cycle impact 0.6409

inventories C3 C2 Remaining value recovery 0.7022

C5 C3 Minimization of 0.6338

environmental mishaps

C7 C4 Use of recycled material 0.6301

A2 Green C8 C5 Internal transport and 0.6318

facilities emissions

C9 C6 Energy use of facilities 0.6924

C10 C7 Emissions of transport 0.6981

units to or from facilities

C11 C8 Congestion around facilities 0.6927

A3 Green C21 C9 Green packaging material 0.7058

packaging C22 C10 Environment-friendly 0.6980

packaging design

C23 C11 Use of cleaner technology 0.6970

in packaging

C24 C12 Third party recycled 0.6895

packaging material

C25 C13 Waste packaging material 0.6916

retrieval

C27 C14 Compliance with 0.7195

international environmental

regulations

A4 Green C31 C15 Use of environment- 0.7053

Transportation friendly technology

C34 C16 Intermodal transport 0.7035

C35 C17 Fuel choice 0.7253

________________________________________________

Threshold 0.6277

________________________________________________

4.2 Reliability of attributes

The attributes’ reliability is checked using BWM based

on the best and the worst criteria under each aspect.

This method is integrated with the FDM in

determining the best and the worst criteria of each

aspect based on the FDM weight as previously shown

in Table 3; the highest weight of the aspect means the

best criterion and the lowest weight of the aspect

means the worst criterion.

Based on the consistency ratio (Ksi), the results

reveal that the evaluated aspects show consistency as

each individual value is close to zero, indicating that

the criteria belong to the aspects and therefore the

measures are reliable, as Table 4 demonstrates below.

Table 4. Verified reliability of green logistics measures

________________________________________________

Aspect Ksi

________________________________________________

A1 Green inventories 0.321231802

A2 Green facilities 0.299065121

A3 Green packaging 0.200488998

A4 Green transportation 0.344497608

________________________________________________

4.3 Causal-effect interrelationships among attributes

The driving and dependent powers are determined by

evaluating the relationships between the valid

attributes using FDEMATEL, which are then depicted

with a graph in a cause and effect diagram. The

experts provide their preferences on the

interrelationships of the aspects utilizing linguistic

scales.

In Figure 2, the causal group consists of green

packaging (A3) and green transportation (A4), while

the effect group consists of green inventories (A1) and

green facilities (A2). The relationship powers vary

among the aspects. For instance, A4, A3, and A2 show

to have a strong effect on A1, while both A3 and A4

have a weak effect on A2.

Figure 2. Cause and effect model of green logistics aspects

The identified important criteria are product life

cycle impact (C1), green packaging material (C9),

intermodal transport (C16), energy use of facilities

(C6), and emissions of transport units to or from

facilities (C7), as depicted in Figure 3.

Figure 3. Causal-effect diagram for criteria

5 DISCUSSION

5.1 Theoretical implication

The results confirm that green packaging is a

determining aspect in terms of making efforts toward

improving GL. A form of packaging that considers

both the preservation of the environment and the

health of people and animals throughout the course of

its lifecycle is referred to as green packaging. The

characteristics of packaging are typically concentrated

on the use of recyclable or reused materials, but they

also include considerations of sizes and shapes for

transportation and stacking effectiveness. Green

packaging potentially rises resource use efficiency by

shortening and decreasing logistics distribution routes

that are otherwise taken for retrieving the raw

material for new production [20]. Yet, the challenge of

green packaging is to achieve the environmental goal

while meeting the economic purpose of protecting

and preserving the product quality and condition

during the logistics processes. In this regard, the firms

adopting GL in their business process are required to

minimize energy use by making the packaging green

through ensuring its high durability and recyclability.

In addition, green packaging is ineffective unless

there is support from laws and policies regulated by

the government in standardizing the minimum

requirement of green packaging for optimal durability

and recyclability [17].

Green transportation is also a vital aspect

pertaining to the causal group which stipulates the

aspect’s importance in strengthening GL. The aspect

refers to saving energy from using any transport

modes throughout the logistics operational activities

[16,31]. The issue of transport choices is heavily

focused on optimizing the routes while considering

lowering the impacts on the environment during the

deliveries [20]. Thus, this study suggests that greening

transportation shall be accomplished by reinforcing

multimodal transportation which appertains to highly

efficient distribution routes hence energy saving. The

use of clean energy and braced environmental

restrictions are a few strategies to promote GL

performance [22]. The highlight of transportation’s

role in GL is put forward due to its main contribution

to emissions generation throughout the logistics

processes, and therefore, by moving forward to green

transportation the goal of GL to eliminate the

environmental impacts in most of its operations can

be achieved effectively. Further, the findings exhibit

strong and moderate effects of green transportation

on green packaging, facilities, and inventories,

suggesting that confirming the whole GL

development and execution is facilitated by greening

logistics transportation.

5.2 Managerial implication

Product lifecycle impact in maritime freight transport

refers to the environmental impacts due to the use of

resources that are required to make the product.

Environmental impact assessment and the

Environmental Protection Agency (EPA) in Taiwan

control the lifecycle impacts of products, including

those moved by water, and demand that maritime

freight transport companies submit strategic

environmental assessment reports to the government.

The main concern is the carbon footprint that is

generated from production and transportation during

the logistics operations which include the marine

operations and those on land. Not only that the

lifecycle impacts need to be reduced but also need to

be properly managed, evaluated, reported, and

controlled with appropriate management. Thus,

logistics firms require management tactics such as

adopting formal operational procedures that are pro-

environment, making reports of logistics activities,

evaluating the firms’ performance, sharing

information, communicating with the relevant

stakeholders about the activities, and complying with

environmental standards. Product lifecycle impacts

are found in the process of producing the product yet

do not end at the end-customers; if the GL concept is

properly applied, the impacts are well monitored and

mitigated by the logistics firms as part of the firm’s

environmental and social responsibility not only on

the production line but more importantly during the

maritime transporting activities. This is in line with

the practice; the maritime freight transport industry

extends the standardized lifecycle assessment by

promoting freight retrieval after use and establishing

an integrated system for further freight treatment

such as for recycling or remanufacturing by

collaborating with other logistics firms, merchants,

customers, and government agencies, in order to

eliminate waste generation.

Green packaging material is found to be

fundamental to improving GL practices for the

maritime freight transport industry, and this criterion

refers to the environment-friendly material used for

packaging during the distribution or delivery

processes. Packaging is crucial as it serves to protect

the freight damage which could lead to product and

financial losses and might potentially break the

relationship or trust between the customers and

logistics service providers. In the maritime freight

transport industry, the transported product is at risk

of physical and wet damages, especially during the

volatile sea conditions during the journey. Green

packaging material does not only need to constitute

material made of recyclates but also be less energy-

requiring during production and reusable by the end-

consumers after the product is received.

Biodegradable and recyclable materials are

recommended for lowering packaging waste

generation. Regarding waste generation, this is in line

with the effort from the government agency where the

Taiwan EPA has collaborated with civic

environmental organizations to set up the so-called

Taiwan Marine Debris Governance Action Plan with a

primary concern of preventing and removing waste

from entering the oceans. Thus, opting for green

packaging material to reduce waste is recommended

for the firms. It has also been highlighted that another

advantage of using green packaging material includes

minimalizing fuel emissions during lengthy trips of

transport; maritime freight transport firms should

consider light packaging materials without neglecting

the safety and protection of the product. In sum,

maritime freight transport firms are suggested to

ensure packaging durability, recyclability, weight,

and versatility in order to implement GL.

The emphasis on the energy use of facilities in

implementing GL of maritime freight transport refers

to achieving zero emission in distributional facilities

including ports and warehouses. In general, these

facilities attribute to a fair cut of the firm’s revenue

due to the use of heating, cooling, and lighting as the

main energy users. The installation of solar panels

and the use of advanced energy-saving technology are

among the common ways that have been done by

many logistics firms within their facilities. For non-

temperature sensitive freight, a well-designed

architectural warehouse that reduces the use of air

conditioning technology can be considered, through

an effective ventilation system. Overall, a proper

energy management system implemented in the

facilities should effectively contribute to the yearly

revenue without needing to take a significant capital

investment. In order to implement GL, logistics

facility managers are encouraged to constantly

improve the facility performance directed toward

shore-power-saving while ensuring the efficiency and

productivity of the operational equipment. However,

adopting a shore power supply system has the

drawback of necessitating investments in relevant

power transmission equipment from both facility

authorities and maritime freight transport firms,

which raises costs. It is challenging to install an

emissions control area to regulate ships and make the

conversion to low-sulfur fuel in the short term. This is

due to the fact that implementing such a plan would

result in higher fuel prices for ship owners and would

require approval from the International Maritime

Organization. Thus, strategies such as lessening the

downtime, extending the equipment lifecycle, and

lowering the power draw during peak periods are

also recommended.

Intermodal transport refers to the use of multiple

carriers that use different modes of transportation to

move freight from the shipper to the consignee and is

facilitated with shared logistics container terminals

that integrate a combination of maritime freight

transport units and inland transport units. The

potential advantage of such an integrated mode of

transport is to save the kilometers that are otherwise

generated in congested routes and thus lower the

environmental impact due to lower emissions

generation. Through enhanced port-to-backcountry

connection, intermodal transportation streamlines the

maritime supply chains for freight transport.

Enhancing intermodal transport to improve the

convergence of maritime freight transport and

logistics requires physical, economic, and

organizational integration involving the infrastructure

and people. In maritime freight transport, the

challenge is that the existing conventional functions of

ports must evolve from enabling loading and

discharging operations to becoming a crucial

connection in a larger logistics chain. At the global

scale, intermodal transport refers to establishing

freight transport corridors that connect different

continents in serving the supply chains which

potentially attract higher demands worldwide.

Overall, implementing intermodal transport in the

maritime freight transport industry requires careful

coordination, focused policies, and investments.

Emissions of transport vehicles or units that

operate to or from facilities refer to emissions

produced by ships or their engines while moored or

operating on less efficient modes. Ship emissions are

predicted to increase over the years depending on the

global future economic and social conditions. The

increasing emission rates are not only due to

inefficiency in keeping the engines on but also driven

by growing demands for freight shipping services and

consumption of fossil fuels. Most berthing ships in

Taiwan operate their boilers and main and auxiliary

engines with heavy fuel oil, which results in severe air

pollution that might have major negative health

effects. In order to decrease emissions from ships at

berth, an efficient mitigation and control plan must be

implemented because this is neither desired nor

sustainable over the long term. Moreover, the increase

in demand also pushes shipping service providers to

improve their performance and one way of achieving

that is through speeding up for faster customer

service, hence higher emissions generation. In-land

transport within the warehouse facilities is also in

question. For example, congestion around facilities

should be reduced by taking advantage of upgraded

technology toward automation, improved inventory

systems, and efficient operational hours. Regulations

at certain cutting-edge facilities require ship owners to

abide by stringent environmental protection laws, and

port authorities ban ships from using their prime

movers when berthed.

In sum, due to the large carbon footprint created

by production and transportation during logistics

activities, including marine and land-based

operations, the maritime freight transport industry

has a substantial impact on the environment. This

impact includes the emissions that ships or their

engines create while moored or using less efficient

modes. The rising demand for freight transport

services and the use of fossil fuels are the main causes

of the rising emission rates. Depending on future

global economic and social conditions, ship emissions

are expected to rise over time. In order to lessen the

industry’s negative environmental effects, green

packaging materials must be used, and energy

efficiency in facilities must be prioritized. By reducing

the number of miles traveled on congested routes,

intermodal transportation can also assist reduce the

production of greenhouse gases. The marine logistical

chains for freight transport may be made more

efficient by the integration of numerous carriers and

shared logistics container ports. Therefore, the

magnitude of the impact can be reduced by

employing appropriate managerial strategies, such as

adopting formal operational procedures that are pro-

environment, reporting logistics activities, evaluating

firms’ performance, sharing information,

communicating with pertinent stakeholders about

activities, and adhering to environmental standards.

6 CONCLUSION

GL develops primarily to lessen the environmental

effects brought on by a series of logistical activities.

Developing GL has not been an easy task due to many

influencing attributes that need to be considered, yet

there is a lack of studies that attempted to identify the

top driving attributes. To solve the gap, this study

overlooks the critical attributes by proposing an initial

hierarchical model of GL attributes containing five

aspects and 35 criteria to be examined using a hybrid

method. FDM was used to screen and validate the

important criteria through an elimination process

using the average value as the threshold. By

comparing the best and worst criterion pairwise,

BWM was used to perform the reliability assessment.

FDEMATEL was applied to determine the driving

aspects and identify the top criteria to improve GL in

the maritime freight transport industry in practice.

Still, the limitations of this study are present. Based

on the literature, this study suggested a set of

attributes and selected them based on a collective

judgment of experts, which is subject to

incompleteness and has the potential to be expanded

by including a wider range of attributes in the future

study. In addition, the future study shall consider the

perspectives of the economy and government to be

included in the proposed framework. Experts in

shipping and logistics who have years of expertise in

the field as well as in academia are involved in this

study; the future study should include a proportional

number of experts from the government as well. In

terms of the industry, this study focuses on the

industry of maritime freight transport which is unique

in its characteristics. The future study should consider

exploring GL in a different kind of industry to enrich

the literature.

REFERENCE

[1] Lee, P.T-W., Hu, K-C., and Chen, T. 2010. “External costs

of domestic container transportation: Short-sea shipping

versus trucking in Taiwan.” Transport Reviews 30: 315-

335. doi:10.1080/01441640903010120

[2] Cordón-Lagares, E. and García-Ordaz, F. 2020. “Factors

affecting the survival of maritime goods transport firms

in Spain.” Research in Transportation Business &

Management 37: 100520. doi:10.1016/j.rtbm.2020.100520

[3] Lau, K.H. 2011. “Benchmarking green logistics

performance with a composite index.” Benchmarking:

An International Journal 18: 873-896.

doi:10.1108/14635771111180743

[4] Liu, J., Zhou, H., and Sun, H. 2019. “A three-dimensional

risk management model of port logistics for hazardous

goods.” Maritime Policy & Management 46: 715-734.

doi:10.1080/03088839.2019.1627435

[5] Notteboom, T., van der Lugt, L., van Saase, N., Sel, and

Neyens, K. 2020. “The role of seaports in green supply

chain management: Initiatives, attitudes, and

perspectives in Rotterdam, Antwerp, North Sea Port,

and Zeebrugge.” Sustainability 12: 1688.

doi:10.3390/su12041688

[6] Cullinane, K., Tseng, Dr P.H., and Wilmsmeier, Dr G.

2015. “The estimation of container ship emissions at

berth in Taiwan.” International Journal of Sustainable

Transportation. doi:10.1080/15568318.2014.975303

[7] Amin, C., Mulyati, H., Anggraini, E., and Kusumastanto,

T. 2021. “Impact of maritime logistics on archipelagic

economic development in eastern Indonesia.” Asian

Journal of Shipping and Logistics 37: 157-164.

doi:10.1016/j.ajsl.2021.01.004

[8] Tseng, P-H. and Ng, M.W. 2021. “Assessment of port

environmental protection in Taiwan.” Maritime Business

Review 6: 188-203. doi:10.1108/MABR-04-2020-0022

[9] EPA. 2016. “Marine pollution control in Taiwan.”

Environmental Policy Monthly 19, 1-12. Accessed

September 5 2022.

https://epa.gov.tw/environmentalpolicymonthly

[10] Fan, C., Hsu, C-J., Lin, J-Y., Kuan, Y-K., Yang, C-C., Liu,

J-H., and Yeh, J-H. 2018. “Taiwan's legal framework for

marine pollution control and responses to marine oil

spills and its implementation on T.S. Taipei cargo

shipwreck salvage.” Marine Pollution Bulletin 136: 84-

91. doi:10.1016/j.marpolbul.2018.09.005

[11] Yazir, D., Sahin, B., Yip, T.L., and Tseng, P-H. 2021.

“Effects of COVID-19 on maritime industry: a review.”

International Maritime Health 71: 253-264.

doi:10.5603/IMH.2020.0044

[12] Hua, J., Wu, Y., and Chen, H. 2017. “Alternative fuel for

sustainable shipping across the Taiwan Strait.”

Transportation Research Part D: Transport and

Environment 52: 254-276. doi:10.1016/j.trd.2017.03.015

[13] Lai, Y-Y. and Lee, Y-M. 2022. “Management strategy of

plastic wastes in Taiwan.” Sustainable Environment

Research 32. doi:10.1186/s42834-022-00123-0

[14] Dekker, R., Bloemhof, J., and Mallidis, I. 2012.

“Operations research for green logistics - An overview

of aspects, issues, contributions and challenges.”

European Journal of Operational Research 219: 671-679.

doi:10.1016/j.ejor.2011.11.010

[15] Shi, W., Xiao, Y., Chen, Z., McLaughlin, H., and Li, K.X.

2018. “Evolution of green shipping research: themes and

methods.” Maritime Policy & Management 45: 863-876.

doi:10.1080/03088839.2018.1489150

[16] Liu, C. and Ma, T. 2022. “Green logistics management

and supply chain system construction based on internet

of things technology.” Sustainable Computing:

Informatics and Systems 35: 100773.

doi:10.1016/j.suscom.2022.100773

[17] Zaman, K. and Shamsuddin, S. 2017. “Green logistics

and national scale economic indicators: Evidence from a

panel of selected European countries.” Journal of

Cleaner Production 143: 51-63.

doi:10.1016/j.jclepro.2016.12.150

[18] de Souza, E.D., Kerber, J.C., Bouzon, K.M., and

Rodriguez, C.M.T. 2022. “Performance evaluation of

green logistics: Paving the way towards circular

economy.” Cleaner Logistics and Supply Chain 3:

100019. doi:10.1016/j.clscn.2021.100019

[19] Agyabeng-Mensah, Y., Afum, E., and Ahenkorah, E.

2020. “Exploring financial performance and green

logistics management practices: Examining the

mediating influences of market, environmental and

social performances.” Journal of Cleaner Production 258:

120613. doi: 10.1016/j.jclepro.2020.120613

[20] Trivellas, P., Malindretos, G., and Reklitis, P. 2020.

“Implications of green logistics management on

sustainable business and supply chain performance:

Evidence from a survey in the Greek agri-food sector.”

Sustainability 12: 10515. doi:10.3390/su122410515

[21] Wang, D-F., Dong, Q-L., Peng, Z-M., Khan, S.A.R., and

Tarasov, A. 2018. “The green logistics impact on

international trade: Evidence from developed and

developing countries.” Sustainability 10: 2235.

doi:10.3390/su10072235

[22] Zhang, W., Zhang, M., Zhang, W., Zhou, Q., and

Zhang, X. 2020. “What influences the effectiveness of

green logistics policies? A grounded theory analysis.”

Science of the Total Environment 714: 136731.

doi:10.1016/j.scitotenv.2020.136731

[23] Chhabra, D., Garg, S.K., and Singh, R.K. 2017.

“Analyzing alternatives for green logistics in an Indian

automotive organization: A case study.” Journal of

Cleaner Production 167: 962-969.

doi:10.1016/j.jclepro.2017.02.158

[24] Kotowska, I. 2016. “Method of assessing the role of

short sea shipping in sustainable development of

transport.” International Journal of Shipping and

Transport Logistics 8: 687-704.

doi:10.1504/IJSTL.2016.79290

[25] Svindland, M. 2018. “The environmental effects of

emission control area regulations on short sea shipping

in Northen Europe: The case of container feeder

vessels.” Transportation Research Part D 61: 423-430.

doi:10.1016/j.trd.2016.11.008

[26] Murphy, P.R. and Poist, R.F. 2000. “Green logistics

strategies: An analysis of usage patterns.”

Transportation Journal 40: 5-16.

[27] Pazirandeh, A. and Jafari, H. 2013. “Making sense of

green logistics.” International Journal of Productivity

and Performance Management 62: 889-904.

doi:10.1108/IJPPM-03-2013- 0059

[28] Bui, T.D., Tsai, F.M., Tseng, M.L., and Ali, M.H. 2020.

“Identifying sustainable solid waste management

barriers in practice using the fuzzy Delphi method.”

Resources, Conservation and Recycling 154: 104625.

doi:10.1016/j.resconrec.2019.104625

[29] Chen, C-C., Sujanto, R.Y., Bui, T.D., and Tseng, M-L.

2022. “Sustainable recyclate packaging in Indonesian

food and beverage industry: a hybrid decision-making

analysis in consumption stages.” Quality & Quantity.

doi:10.1007/s11135-022-01458-x

[30] Aliabadi, M.M., Mohammadfam, I., Soltanian, A.R., and

Najafi, K. 2022. “Human error probability determination

in blasting process of ore mine using a hybrid of HEART

and best- worst methods.” Safety and Health at Work 13:

326-35. doi: 10.1016%2Fj.shaw.2022.03.010

[31] Mohsin, A.K.M., Tushar, H., Hossain, S.F.A., Chisty,

K.K., Iqbal, M.M., Kamruzzaman, M., and Rahman, S.

2022. “Green logistics and environment, economic

growth in the context of the Belt and Road Initiative.”

Heliyon 8: e09641. doi:10.1016/j.heliyon.2022.e09641

[32] Khan, S.A.R., Zhang, Y., Anees, M., Golpîra, H.,

Lahmar, A., and Qianli, D. 2018. “Green supply chain

management, economic growth and environment: A

GMM based evidence.” Journal of Cleaner Production

185: 588-599. doi:10.1016/j.jclepro.2018.02.226

[33] Yingfei, Y., Mengze, Z., Zeyu, L., Ki-Hying, B. Avotra,

A.A.R.N., and Nawaz, A. 2022. “Green logistics

performance and infrastructure on service trade and

environment-measuring firm's performance and service

quality.” Journal of King Saud University - Science 34:

101683. doi:10.1016/j.jksus.2021.101683

[34] Panayides, P.M. and Song, D-W. 2013. “Maritime

logistics as an emerging discipline.” Maritime Policy &

Management 40: 295-308.

doi:10.1080/03088839.2013.782942

[35] Halim, R.A., Kwakkel, J.H., and Tavasszy, L.A. 2016. “A

strategic model of port-hinterland freight distribution

networks.” Transportation Research Part E 95: 368-484.

doi:10.1016/j.tre.2016.05.014

[36] Álvarez-SanJaime, Ó., Cantos-Sánchez, P., Moner-

Colonques, R., Sempere-Monerris, and J.J. 2013. “Vertical

integration and exclusivities in maritime freight

transport.” Transportation Research Part E 51: 50-61.

doi:10.1016/j.tre.2012.12.009

[37] Wiegmans, B. and Janic, M. 2019. “Analysis, modeling,

and assessing performances of supply chains served by

long-distance freight transport corridors.” International

Journal of Sustainable Transportation 13:278-293.

doi:10.1080/15568318.2018.1463419

[38] Facchini, F., Digiesi, S., and Mossa, G. 2020. “Optimal

dry port configuration for container terminals: A non-

linear model for sustainable decision making.”

International Journal of Production Economics 219: 164-

178. doi:10.1016/j.ijpe.2019.06.004

[39] Marlina, E., Hidayanto, A.N., and Purwandari, B. 2022.

“Towards a model of research data and management

readiness in Indonesian context: An investigation of

factors and indicators through the fuzzy delphi

method.” Library & Information Science Research 44:

101141. doi:10.1016/j.lisr.2022.101141

[40] Ishikawa, A., Amagasa, M., Shiga, T., Tomizawa, G.,

Tatsuta, R., and Mieno, H. 1993. “The max-min Delphi

method and fuzzy Delphi method via fuzzy

integration.” Fuzzy Sets and Systems 55: 241–253.

doi:10.1016/0165-0114(93)90251-C

[41] Soner, O. 2021. “Application of fuzzy DEMATEL

method for analysing of accidents in enclosed spaces

onboard ships.” Ocean Engineering 220: 108507.

doi:10.1016/j.oceaneng.2020.108507

Appendix A

Initial attributes

___________________________________________________________________________________________________

Aspect Initial Criteria Description

code

___________________________________________________________________________________________________

A1 Green 1 Life cycle impact Life cycle impact indicates the resources that generate carbon

inventories footprint during transport

2 Distance to fabrication The distance of product to its fabrication affects the carbon

footprint trace

3 Remaining value recovery Recovering the remaining value of a product, instead of

landfilling or incinerating

4 Returnable transport items Returnable transport and packaging supply such pallets,

containers, and roll cages

5 Minimization of Reduction of trash production, poisonous and dangerous

environmental mishaps material consumption, and environmental accidents

6 Products environmental The environmental impacts of products

impacts

7 Use of recycled material The volume of recycled material used

A2 Green 8 Internal transport and If emissions from transport in container ports can be decreased,

Facilities emissions the environment will benefit

9 Energy use of facilities Many firms are concerned about the energy usage of buildings

like warehouses, and not just for financial reasons

10 Emissions of transport Emissions from vehicles near or inside of buildings, such as

units to or from facilities when a ship is docked and has its engines running

11 Congestion around Peak arrival times are caused by connection times for

facilities transshipping products, and if there are any disruptions, there

may be extended waiting hours

12 Reduction of warehouse fee Fee for using warehouse

13 Location selection of Selecting an optimal location of warehouse

warehouse

14 Product storage The supply chain's design must take inventory holding costs

into consideration

A3 Green social 15 Health and safety of Improved health and safety for employees

performance employees

16 Community health and Increased community safety and health

safety

17 Employees' skills Improved skills of the employee

18 Employees' job satisfaction Improved levels of work satisfaction among employees

19 Stakeholders' knowledge Increased engagement of stakeholders in planning and carrying

in green activities out environmental practices and improvement of their

awareness of green activities

20 Reputation and market Enhanced company's reputation and image in the market

image of the company

A4 Green 21 Green packaging material Use of green material for packaging

packaging 22 Environment-friendly Packaging that uses environmentally friendly design

packaging design

23 Use of cleaner technology Packaging using greener technology

24 Third party recycled Use of recycled packaging acquired outside of the company

packaging material

25 Waste packaging material Collecting used packaging from consumers for recycling

retrieval

26 Packaging material amount Amount of packaging material to be used

27 Compliance with Packaging that complies with international environmental

international environmental requirements

regulations

A5 Green 28 Use of energy efficient Utilizing energy-efficient vehicles to increase efficiency

transportation vehicles

29 Optimization of Enhancement of the distribution process through improved

distribution process scheduling and routing

30 Use of integrated delivery Using integrated delivery to cut down on travel

31 Use of environment- Use of green technology in transportation

friendly technology

32 Reverse material flows Reverse material flows are managed to minimize transportation

33 Unit load After selecting a method of transportation, a decision must be

taken on the kind and dimensions of the transportation unit

34 Intermodal transport Transporting freight utilizing several different means of

transportation while using an intermodal container or truck

without handling the freight individually

35 Fuel choice The selection of an environmentally friendly fuel

___________________________________________________________________________________________________

Appendix B

Experts’ characteristics

___________________________________________________________________________________________________

Expert Position Education level Years of experience Expertise

___________________________________________________________________________________________________

1 Senior research commissioner PhD 36 Shipping and commercial ports

2 Deputy director PhD 29 Shipping and commercial ports

3 Deputy Masters 12 Shipping and commercial ports

4 Manager Masters 20 Stevedoring & warehousing

5 Head of department Masters 10 Harbor management

6 Head of department Masters 12 Ship & machinery

7 Supervisor Masters 7 Stevedoring & warehousing

8 Deputy PhD 21 Trading Policy – Ministry of Trade

9 Head of department PhD 16 Trading Policy – Ministry of Trade

10 Head of department PhD 12 Trading Policy – Ministry of Trade

11 Manager Masters 13 Customs and Logistics

12 Supervisor Masters 7 Customs and Logistics

13 Chair professor PhD 30 Sustainable supply chain

14 Professor PhD 22 Sustainable supply chain

15 Professor PhD 14 Marine transportation science

16 Associate professor PhD 11 Shipping & transportation management

17 Associate professor PhD 9 Sustainable/Green logistics

___________________________________________________________________________________________________