Inventory

1. Factors that Influence Container Inventory Management
Strategies
Lalith Edirisinghea,b, Zhihong Jinb, A.W. Wijeratnec
aColombo International Nautical and
Engineering College – CINEC Campus,
Millennium Drive, IT Park, Malabe, Sri Lanka
lalith.edirisinghe@cinec.edu
bDalian Maritime University,
No. 1 Linghai Rd, Ganjingzi,
Dalian, Liaoning, China
jinzhihong@dlmu.edu.cn
cSabaragamuwa University of Sri Lanka, Sri Lanka
aw.wijeratne@gmail.com
Abstract
This paper addresses an existing gap in the literature because majority or researches have focused
attention of smart container reposition rather than minimizing the cost of container shipping through
effective and efficient container inventory management strategies. It initially discusses 6 common
container inventory management strategies and investigates the factors that potentially influence
carriers’ container inventory management strategies. It explores 10 key factors that may impact the
carriers’ container inventory management strategies. Usually, the demand and supply of containers are
not rightly balanced in a port. As a result, the carriers incur a substantial cost in managing their
containers. Therefore, carriers need highly effective and efficient container inventory management
system to minimize these costs. The carrier’s reslilience or Cost of Customers; Potential threats on
Service sustainability; Loss of Revenue due to non-availability of containers; Slot Cost incur to carry
empty containers; Port Handling costs for empty containers; Cost of Rent; Cost of Yard; return on
investment of containers; Ware and Tare cost; and container idle time are considered to be significant
while the impact on Brand name the vessel underutilization are found unrelated to current container
management strategies. The paper appeals the carriers the need for a contemporary appraisal of
container inventory management strategies and reduce the exorbitant cost that is incurred on empty
container repositions globally.
Keywords: containers, inventory, management, shipping lines
Introduction
Containerisation
6th International Conference on Management and Economics
09th & 10th November 2017
Faculty of Management and Finance, University of Ruhuna, Sri Lanka

2. Shipping is a business that grew up with the world economy, exploring and exploiting the ebb and flow of trade
(Stopford, 2009). Shipping is a derived demand of international trade in economic terms. (Edirisinghe & Ratnayake,
A, 2015). The container help reduce the global supply chain cost (Edirisinghe, Jin, & Wijeratne, 2016 b). From 1981 to
2009, global transport of containerized cargo increased approximately 3.3 times faster than the world’s GDP (UNCTAD
secretariat, 2011). World’s very first all-container ship “Gateway city” was found in 1950 (Cudahy, 2006) and
containerization was commercially implemented in the US in the mid-1950s (Bernhofen, et al., 2013) and is the driver
of the twentieth century economic globalization and world container port throughput increased by an estimated 3.8 per
cent to 601.8 million 20-foot equivalent units (TEUs) in 2012 (UNCTAD, 2013). Containerization was not just about
ships but a new way of organizing transport (Stopford, 2009) has made a momentous change globally in the system of
freight transport. However, container fleet size and the complexity of the container shipping network (Dong, et al.,
2013) have increased dramatically bringing more challenges to the operation of the container shipping system. Cross-
border transportation is an engine to promote the foreign trade (Zhihong & Qi, 2012). The system, that proved its
potential as an increasingly efficient and swift method of transport, led to greatly reduced transport costs, and
supported a vast increase in international trade.
Container Inventory Imbalance
Commercial traffic never seems to be in balance (Yur & Esmer, 2011). Therefore, container inventory imbalance (CII)
is inevitable and is a global issue. Very rarely the shipping lines have a well-balanced container inventory due to many
practical reasons such as international trade patterns and the consequence of imbalances in the worldwide trade
distribution (Karmelic, et al., 2012), uncertainties of customer demands, widespread allocation of container ports and
customers, and the dynamic nature and increased complexity of the container shipping (Dong, et al., 2013) and the type
of commodities to be moved etc. A balanced inventory may realise only when the exporters’ demand for containers are
equal to the laden containers imported into the country which is very unlikely given the above circumstances. Providing
containers help increase the utilization rate of containerships. (Rodrigue, 2013) Therefore the right balances of
‘Container inventory’ at a given location are a vital factor in liner shipping. With respect to deficit ports the container
shipping lines (CSL) tend to sail their ships with vacant space. In instances where the number of laden containers
imported in to a port is lesser than the number of laden containers the CSL exports from that port a ‘deficit’ exists. The
right balance of ‘Container inventory at a given location is a vital factor in liner shipping. Due to the perishability factor
in liner shipping services the underutilized ship space is lost forever and cannot be reused later. Usually, demands for
empty containers and the arrivals of laden containers to be reused will not match (Song & Carter, 2009). Shipping is
highly sensitive with respect to timely delivery of cargo thus availability of containers is vital as much as availability of
ships. Usually carriers pass the additional cost incurred owing to having transport empty containers to the customer
(i.e. shipper or consignee). This cost is either recovered as a part of freight charges or as a surcharge. For example,
Maersk Line, (2013) once announced that the Equipment Imbalance Surcharge has been implemented due to an
increasingly severe equipment imbalance at Toronto container yards, leading to significantly higher empty
repositioning costs.
Container Inventory Management
A container designed primarily for the use and re-use in the transport of goods. Therefore, it has to be able to be
transported and re-transported several times before its life-time comes to an end. As cited in [21], containers remain
for about half the time of their lifetime being idle as they are either being maintained, repaired or in storage or in transit.

3. The container supply chain of a CSL is illustrated in figure 1 The MTY stocks also occupy ground space used for storage
thus creating recognizable environmental hazards.
Figure 1 : Container supply chain of a CSL
In liner shipping, therefore, the demand for shipping is subject to fluctuations in world trading patterns. The supply of
shipping capacity, therefore, is subject to volatility in demand in shipping. Cargo cannot be shipped without containers
to carry the cargo and, therefore, the supply of shipping facilities cannot be materialized only by making the ship space
(slot) available for the exporter. Therefore MTYs should be made available at each port that the ships are scheduled to
call. Ideally the available quantity of MTY should be equal to the space (slots) available in the ship.
CSL try to mitigate the negative impact of CII mainly through internal controls. For example, some lines (principals)
penalize their regional offices and agents for any idle containers remain in their respective territories. Usually, container
liner shipping is heavily relying on long term forecasting of imports and exports to each port they service. The most
effective container inventory management (CIM) system is to organize the flow of export containers aligned with the
same of import containers. However, it is easier said than done mainly due to several types (general purpose, high cube,
reefer, open top, flat rack etc.) and multiple sizes (20’, 40’, 45’ etc.) of containers in circulation. In economic terms, the
shipping industry is governed by derived demand characteristics. Therefore, CSL basically have no control of the
quantity of containers imported to and exported from a particular port. In order to be competitive in the market the
carriers need to cater to the changing demands of the customers. Unlike in the break bulk shipping, the container
shipping supply cannot be fulfilled by operating ships alone. It needs containers in which the intended export cargo
would be stuffed before loaded on board the vessel. These complimentary factors make the CIM a crucial role and vital
activity as equal as managing the shipping space (slots in cellular vessel).
Research problem

4. Improving logistics performance has become an important development policy objective in recent years (Edirisinghe,
2013). Alderton, (2004) estimated that 22% of container cost are originated from the container inventory imbalance.
Container freight rates have always been reflecting a declining trend while costs of carriers are increasing. There is a
serious gap in the shipping industry about comprehensive research and developments on effective and efficient
container inventory management. It is also significant to note that most of the previous literature had focused its
attention to minimize the “cost of repositioning” per empty container. In other words, the existing literature is limited
to smart repositioning of empty containers but not to reduce the “need” to reposition empty containers. In considering
the ground reality, this paper attempts to explore the factors that influence carriers’ container inventory management
strategies based on the experts’ opinion in container shipping industry.
Edirisinghe, Jin, & Wijeratne, (In press) investigates, the strategies that are currently used by shipping lines to manage
their container inventories efficiently and effectively. This paper is an extension to evolving research interest on CIM.
Accordingly, it questions the potential factors that may potentially impact six CIM strategies that were identified in
previous research.
Review of the relevant literature
The globalization has increased the need for interconnectedness for the respective countries to cross their borders
(Edirisinghe, 2013). Logistics and supply chain cost reduction has become the focus for companies and after
containerization the container logistics plays a dramatic role in global supply chain. Transportation is the web that links
people, cultures, cities, towns and villages in to a one common network of relationships (Edirisinghe & Rodrigo, 2015)
"The best way to describe logistics is waste," If you can squeeze that waste of the system then you can tactically improve
your profit margins" (Bennett, 2013). Containerisation has revolutionised the way in which firms transport their goods
around the world (Lai, et al., 2012) however, at least half of the boxes moving westward to Europe were sent back empty.
Directional imbalances in trade activities result in a surplus or shortage of empty containers in ports and depots (Olivo,
Zuddas, & Di Frances). Imbalances in supply and demand patterns for empty containers have created certain logistic
challenges in the yield management of container transportation services (Li, et al., 2004). Therefore, the reduction of
empty container movement will reduce fuel consumption, and reduce congestion and emission (Song & Dong, 2014).
Karmelic, et al., (2012) suggest six factors that should be considered by carriers to optimize their empty container
logistics. Those factors include trade imbalances between particular markets in determining liner service; the type of
container equipment available in determining container capacities based on the ratio between the number of a carrier’s
own containers and those to be leased; the optimal leasing arrangement category if containers are leased; the
availability of new containers for purchase; optimal repositioning routes; and special empty-container repositioning
tariffs and storage tariffs imposed by container terminals and depots.
Container management is resource-intensive (Thoroe, Melski, & Schumann, 2009). Empty container management can
be thought of as a minimum cost flow problem whose arcs represent services routes, inventory links and decisions
concerning the time and place to lease containers from external sources (Olivo, Zuddas, & Di Frances). Savi, (2016)
proposes a five-step approach that helps companies make their container supply chains more efficient. It includes,
understanding (map) the container management process; identify the pain points; identify and fill in information gaps;
monitor key performance indicators (KPIs); and data mining and analytics. It further emphasises on ranking the areas
that causes the greatest pain such as container utilization; transportation and warehouse space management.

5. The total sum spent on repositioning of an empty container (MTY) is a complex calculation because the
cost parameters are numerous and varied(Edirisinghe, Zhihong, & Wijeratne, 2015)Developing concepts for
collapsible or foldable containers might represent a solution to minimize both regional and international movement.
The potential cost savings of operating collapsible containers extends beyond decreasing marine and surface transport
costs: because several empty containers can be folded and handled in one package, incremental break-down and
assembly costs can be offset with the efficient use of space (at terminals and aboard ships) and reduced trucking,
handling, and storage costs (Hanh, 2003). Another application being practiced is a flexible destination port policy. This
type of policy only specifies the direction of the MTY flows, whereas ports of destination are not determined in advance,
and MTYs are unloaded from vessels as needed (Song & Dong, 2011). The effectiveness of this method is limited to the
relevant line’s service routes, container inventory and fleet size. Song and Carter (Song & Carter, 2009) propose external
container sharing as a strategic option that involves pooling container fleets among various ocean carriers. Another
study conducted by Francesco, et al., (2009) shows that multi-scenario policies require shipping companies to satisfy
empty-container demands for different values that may involve uncertain parameters. Feng & Chang, (2010) have
formulated a model that incorporates the expected cost of MTY repositioning subject to constraints of vessel capacity,
container demand and MTY supply. In current practice, off-hired empty container movements are often more flexible
than those of carrier-owned empty containers (Hanh, 2003). Container leasing is part of a carrier’s inventory
management strategy. Carriers prefer to lease containers in shortage areas and off-hire them in surplus areas to avoid
repositioning costs (Hanh, 2003). Di Francescoa, et al., (ND) propose a mathematical model to minimize the overall
cost of managing empty containers using the day as a time-step of a dynamic network over a planning horizon of fifteen
days.
It is appropriate discuss those strategies prior to investigate the factors that may influence such strategies.Edirisinghe,
Jin, & Wijeratne, (In press) and(Edirisinghe, Zhihong, & Wijeratne, 2016)propose six CIM strategies that may be
adopted by carriers. These strategies include,
1. Derive accuracy of forecast through Service agreements with customers
2. Synchronize the annual budget of each shipping agent with the monthly forecast of respective port pairs
3. Customer focus Agile inventory irrespective of its associated cost
4. Reduce import freight in response to foreseeable deficit at a specific destination
5. Reduce export freight in response to foreseeable excess at a specific origin
6. Priority for Exporters that is facilitated through unlimited empty repositioning
Accordingly, the factors that influence above strategies need to be investigated. Increases in the efficiency of container
utilization can only be achieved if carriers more efficiently manage the origins and destinations of their cargo bookings
and the operation of their equipment depots, are more careful about where and when they will position empty
containers, and develop stricter regulations about how long customers can wait to pick up their cargo or store containers
without paying a fee (W.S.C, 2011). The CIM decisions are usually influenced by many factors (Edirisinghe,
Zhihong, & Wijeratne, 2016a). However, there is no standard fool proof CIM system that could effectively
and efficiently control these factors is in place.
Methods

6. This study was conducted in Sri Lanka with the intention of generalizing its outcome in the global context. The
researchers are confident that results could be generalized for the benefit of global shipping communality given the
maritime background in Sri Lanka. Seventeen out of top twenty CSL in the world operate regular services in the busiest
commercial port in the country, Colombo; this is primarily due to the country’s strategic geographic location.
Approximately 75 percent of global container capacity is operated (alphaliner.com, 2016) by the said carriers.
Therefore, the sample is expected to be fairly reflective to the general view of the global shipping industry.
CSL have no standard practices or commonly known strategies for CIM. The carriers usually deploy their individual
mechanisms and in most cases the “container controllers’ job is considered a profession based on tacit knowledge.
Therefore, the best way to find out those strategies is the depth interviews with those who closely involved in the
container supply chain. The interviews were conducted using 30 senior representatives (comprising administration,
marketing, and container control and vessel operations departments) of CSL. The responses were tabulated and the
questions for the survey have been developed based on the information received in the exploratory study. It was
identified that 12 factors may influence the carriers CIM strategy. The questionnaire comprising these 12 factors was
developed and the survey was then carried out to collect some specific data covering the entire shipping industry. This
was done through emails and interviews. Respondents were required to mark their preferences in all questions fewer
than eleven scales of score ranging from +5 to -5 representing highly agree to highly disagree respectively and neutral
(0). Questionnaire was made very brief and deliberately in objective form given the nature of respondents and based
on previous experiences. The employees in the shipping industry in Sri Lanka usually show low interest to participate
in surveys. Accordingly, only 72 out of the sample of 105 have been responded. The responses of the questionnaire
survey have been analysed using descriptive statistics and regression analysis. The questionnaire was focused on the
factors that have a potential influence on the CIM strategies.
Table 01: The factors that may influence carriers CIMS
Factors that are potentially influencing the CIM strategies (FIS) Abbreviation
The strength of retaining customers irrespective of non-availability of containers (Cost of
Customers)
COC
Impact on brand name due to inconsistency of container availability (Impact on Brand) IOB
The threat caused by container shortage to the sustainability of service (Threat on Service) TOS
The degree of confidence to perform budgeted exports/imports (Loss of Revenue) LOR
Comfort on freight (Slot cost) incurred on empty repositioning (Empty Slot Cost) ESC
Port handing cost incurred on empty repositioning (Empty Port Handling) EPH
High rent involved at Container Freight Stations (CFS) or port for storage of containers (Cost of
Rent)
COR
Comfort on empty container handling cost at CFS (Cost of Yard) COY
The degree of possibility of achieving ROI-return on investment of containers belong to the shipping
line
ARI
Comfort on repair and painting cost due to rust etc because of long storage (Ware and Tare cost) WTC
The container idle time at a named location (Minimum Idle Time) MIT
Vessel underutilization in certain ports due to non-availability of containers (Vessel
underutilization)
VUN

7. Data analysis
Regression analyses on twelve questions have been carried out to determine the significance of these factors to the
various strategies.
Table 2. Regression equations for six CIM strategies
Service
Agreements=
t P Budget
Synchronize
=
t P Inventory
Agile =
t P
- 1.76 + 1.49
COC
4.20 <0.001 - 2.60 + 1.73
COC
3.95 <0.001 6.50 - 1.92
COC
-11.87 <0.001
1.12 + 0.78
COY
3.94 <0.001 - 4.23 + 1.76
LOR
3.09 0.003 2.82 - 1.05
COY
-11.47 <0.001
- 1.08 + 1.12
ARI
3.06 <0.001 - 0.884 +
0.93 ESC
3.57 0.001 6.23 - 1.69
ARI
-8.95 <0.001
- 3.81 + 1.71
LOR
2.98 0.004 - 1.53 + 1.16
EPH
2.08 0.041 5.03 - 1.20
ESC
-8.52 <0.001
- 1.18 + 1.19
COR
2.86 0.006 - 1.81 + 1.31
ARI
3.67 <0.001 6.27 - 1.74
COR
-7.54 <0.001
- 0.030 + 0.70
ESC
2.57 0.012 - 1.94 + 1.38
COR
3.43 0.001 7.95 - 1.84
LOR
-4.95 <0.001
- 2.55 + 1.43
WTC
2.56 <0.001 0.772 + 0.89
COY
4.63 <0.001 3.81 - 0.755
MIT
-4.36 <0.001
- 1.66 + 1.31
EPH
2.37 0.021 - 5.33 + 1.90
TOS
3.74 <0.001
0.25 +
0.62MIT
2.32 <0.001 4.79 - 1.09
EPH
-2.81 <0.001
Freight
Drop Imports
=
t P Freight
Drop Exports
t P Priority for
Exports =
t P
5.63 - 1.32
COC
-14.91 <0.001 6.16 - 1.45
COC
-11.50 <0.001 - 0.393 + 0.88
COY
3.67 <0.001
3.07 - 0.69
COY
-12.32 <0.001 3.32 - 0.73
COY
-8.96 <0.001 - 3.74 + 1.64
COR
3.37 <0.001
4.67 - 0.84
ESC
-10.43 <0.001 4.96 - 0.87ESC -7.73 <0.001 - 3.34 + 1.45
ARI
3.34 <0.001
5.08 - 1.02
ARI
-7.81 <0.001 5.40 - 1.05
ARI
-6.23 <0.001 - 3.08 + 1.44
COC
3.25 <0.001
5.11 - 1.05
COR
-6.74 <0.001 5.46 - 1.10
COR
-5.59 <0.001 11.3 - 2.84
TOS
10.49 <0.001
3.80 -
0.53MIT
-4.84 <0.001 6.98 - 1.31
LOR
-4.50 <0.001 - 2.18 + 0.98
ESC
3.07 0.003
6.13 - 1.11 LOR -4.55 <0.001 4.02 - 0.53
MIT
-3.89 <0.001 - 1.29 + 0.66
MIT
2.07 0.043
5.08 -
0.99EPH
-4.20 <0.001 5.53 - 1.08
EPH
-3.79 <0.001

8. - 2.67 + 1.41
TOS
3.60 0.001
Note: t is significant test for the regression coefficient and P indicates the level of significance
Source: research data
The column 1 of table 2 illustrates the regression results between the service agreement strategy and LOR, COY, ARI,
LOR, COR, ESC, WTC, EPH, and MIT. The F statistics are significant at <0.05 for all the variables in the table. The
relationship between the strategy (dependent variable) and the predictors (independent variables) of each case is
statistically significant at <0.05, and the relationships are positive. Given carriers’ ability to negotiate more beneficial
terms with stakeholders such as ports, CFS will tend to attract more long-term service contacts with customers. It was
also noted that the carriers also strategically reduce freight rates for their exports originating from a port to control
their container inventory imbalance. This approach is more reactive nature in response because it is usually
implemented when a port accumulates empty containers because of unexpected changes in the market. Except for Q40,
which relates to the strength of service sustainability (Threat to Service). The column 5 provides the regression equation
for this factor. It shows the regression results between Freight Drop Export and COC, COY, ESC, ARI, COR, MIT, LOR,
EPH, and TOS. The F statistic is significant at P < 0.001 for all the variables in the table. The relationship between the
two variables for all cases is negative (except “threat on service” which is positively related) and significant at P < 0.001.
These scenarios are illustrated in Figure 2
COC
LOR
EPH
ESC
COR
ARI
MIT
WTC
TOS
Service Agreements
Freight Drop Exports
Figure 2: Factors that impact Freight drop exports and Service agreements

9. Usually, the shipping forecasts are directly related to global trading patterns because shipping is a derived demand if
international trading. Carriers work very closely with their agents in every port/location to derive the most realistic
forecasts on a long-, medium- and short-term basis. When each agent’s annual budget is synchronized with these
forecasts, the agents are heavily and consistently accountable to perform with no or minimal variation. Some carriers
expect their agents to maintain 90-95% consistency between the annual budget and the cumulative export/import
monthly forecasts. The regression results in column 2 of table 2 (and figure 3) provide the relationship between the
budget-synchronization strategy and COC, ESC, EPH, ARI, COR, and MIT.
COC
EPH
ESC
COR
ARI
MIT
Budget Sincronization
Figure 3: Factors that impact Budget synchronization strategy
There is major competition among carriers in the liner shipping industry. Therefore, container carriers are usually very
careful about customer service. The carriers always attempt to maintain agile container inventory levels considering
the volatile nature of demand for shipping. Accordingly, Except for the strength of sustainability of service, all the other
predictors in the column 3 are inversely related. The regression equation results between Inventory Agile and COC,
COY, ARI, ESC, COR, MIT, LOR, and EPH are presented in this column. The F statistic is significant at 0.000 for all
the variables (except 0.006 for empty port handling) for this factor. The relationship between the two variables for all
cases is negative (except for the strength of sustainability of service , which is positively related) and significant at 0.000
(<0.05). this relationship is illustrated in figure 4.

10. LOR
Freight drop-Imports
&
Inventory agile
COC
EPH
ESC
COR
ARI
MIT
COY
Figure 4: Factors that impact inventory agile strategy
In table 2, the column 4 refers to the regression equation for Freight Drop Import (dependent variable) and COC, COY,
ESC, ARI, COR, MIT, LOR, and EPH (independent variables). The F statistic is significant at 0.000 (<0.05) for all the
variables. The relationship between the two variables in each case is negative. For example, more the carrier is resilient
about customer attrition (COC), lesser it tends to drop import freights. If the carrier is comfortable with respect to
container freight station (CFS) cost, or slot cost for empty container reposition (ESC), or port handling cost (EPH),
there will be a lesser tendency towards reducing import freight. Similarly, when the cost of rent is higher (COR), lesser
the carrier’s interest towards reducing import freight and allow containers accumulated in the respective port. Same
applies for MIT as idle time is negatively related with import rate drop.
Column 6 of the table 2 explain the relationship between giving priority for exporters and COC, COY, ESC, ARI, COR,
MIT, and TOS. According to this strategy, carriers tend to prioritize exports originating from a port and make all
container-related operational decisions in a manner that facilitates those efforts. Notably, when the idle time of
containers at a given port is high, carriers tend to prioritize exports from that location. This relationship is illustrated
in figure 5.

11. COC
COR
ESC
COY
ARI
MIT
TOS
Priority for Exports
Figure 5: Factors that impact “Priority for exporters” strategy
Results and discussion
This research proposed 12 factors that may influence carriers’ CIM Strategies. According to statistical analysis the paper
has identified 2 strategies that could be influenced by 9 factors. Accordingly, Service Agreements (Derive accuracy of
forecast through Service agreements with customers); and Freight Drop Exports (Reduce export freight in response to
foreseeable excess at a specific origin) are influenced by 9 factors out of 12 factors identified in the paper. In other
words, carriers’ Service Agreements strategy is influenced by COC; LOR; ESC; EPH; COR; COY; ARI; WTC; and MIT.
The strategy of “Freight Drop Exports” could be influenced by COC; LOR; ESC; EPH; COR; COY; ARI; TOS; and MIT.
Similarly, all CIM strategies could be influenced by 5 factors namely, COC; ESC; COR; COY; and ARI. Therefore, the
carriers’ strength of retaining customers irrespective of non-availability of containers (Cost of Customers) abbreviated
above as COC ; the carriers’ comfortability on meeting the freight (Slot cost) incurred on empty repositioning (Empty
Slot Cost or ESC); the cost of rent involved at Container Freight Stations (CFS) or port for storage of containers (Cost
of Rent or COR); carriers’ convenience with regard to empty container handling cost at CFS (Cost of Yard or COY); and
the degree of possibility of achieving ROI-return on investment of containers belong to the shipping line (ARI) are
considered most influential factors.
It was identified that carriers’ may reduce import freight in response to foreseeable deficit at a specific destination
(Freight Drop Imports). This strategy could be influenced by 8 factors namely, COC; LOR; ESC; EPH; COR; COY; ARI;
and MIT that was considered in this research. Other 3 CIM strategies namely, Budget Synchronize; Inventory Agile;
and Priority for Exports may be influenced by 7 factors each. It was also noted that 2 out of 12 factors that was
considered in this research were found statistically not significant.

12. Conclusion
The paper investigated the statistically significant relationship between 6 CIM strategies and 12 factors that may
influence the said strategies. Accordingly, the impact on brand name due to inconsistency of container availability
(Impact on Brand or IOB) and the vessel underutilization in certain ports due to non-availability of containers (Vessel
underutilization or VUN) have no relationship with any CIM strategies of carriers. Also, none of remaining factors
proved a relationship with all CIM strategies. The paper concludes that carriers’ 2 CIM strategies namely, the service
Agreements (Derive accuracy of forecast through Service agreements with customers); and Freight Drop Exports
(Reduce export freight in response to foreseeable excess at a specific origin) would be influenced the highest number of
factors.
The 12 factors considered in this study reflect the overall characteristics of individual carriers’ inventory levels,
negotiation capability with various service providers such as port terminals, CFS, vessel operating common carriers
(VOCC) etc. in different ports. The beauty is that a carrier may react differently in two ports irrespective the size of the
total container fleet dispersed globally. For example, a mega carrier may respond like a small player in a port when her
activities only make a moderate impact on the overall shipping scenario. This reality is very crucial with respect to CIM
strategies because any of the 12 factors could lead carriers adopting the one or more of CIM strategies identified in this
paper. Therefore, carriers may carefully evaluate what strategies they should prioritize and what factors that may
influence their individual decision.
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