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JOURNAL OF INTERDISCIPLINARY RESEARCH

which will not jeopardize the quality of products and services.
Author Lu conducted research for an algorithm for dynamic
order-picking in warehouses, and according to it, the dynamic
order-picking strategies that allow changes of pick-lists during a
picked cycle are of importance (Lu et al. 2016).

Warehouse operations are critical for each supply chain.
According to some authors, the efficiency and effectiveness of
the supply chain network depends on warehousing operations
and its performances (Rouwenhorst et al. 2000). Different
methods of order-picking, equipment or information technology
could be used for improving order-picking process. It is well
known that implementation of Warehouse Management System
(WMS) means integration in day-to-day planning and
controlling processes. This software system presents a great
support to warehousing process. Before WMS companies were
using Inventory Control System. But WMS has greater results in
terms of functionality and optimisation routines (Moellera,
2011).

We cannot forget about the difference between Warehouse
Management System (WMS) and stock control. Under stock
control we understand goods, their volumes, arrival at the
warehouse, dispatching etc. Warehouse Management System
manages works at the warehouse and hence differs from stock
control. Warehouse management is carried out based on set of
algorithms, which work with entrance data and set of rules,
while system based on delivery not and orders receives
determines where the items received will be stored, or from
where it will be dispatched. Also it takes into account principles
of FIFO (First In, First Out), LIFO (Last In, First Out), FEFO
(First Expired First Out). Warehouse Management System
generates expenses, manages movements of warehouse keepers
in the warehouse, manages work of warehouse keepers and
compares their performances with time data optimised for given
operation.

Warehouse Management System works with storage positions,
one-level and multi-level packaging which enables to monitor
individual storage movements. In application of system
management there are combined also other technologies
assisting to decrease error rates and save time. There we include
for example RFID, Pick by Voice, Pick by Light, conveyors and
others. Radio Frequency Identification (RFID) has been
identified as a crucial technology for the modern 21

century

knowledge-based economy. Some businesses have realised
benefits of RFID adoption through improvements in operational
efficiency, additional cost savings, and opportunities for higher
revenues. RFID research in warehousing operations has been
less prominent than in other application domains (Ming et al.
2013). The sensor-based method uses a RFID tag (Jeon et al.
2010), a laser pointer, a wireless sensors (Shen et al. 2015) and a
laser sensor (He et al. 2010; Lecking et al. 2006) for pallet
detection and location. RFID is composed of a couple reader /
tag. The reader sends a radio wave, the tag in turn sends an
identification frame. Once the chip is powered, labels and tags
communicate following the TTF protocol (Tag Talk First) or ITF
(Interrogator Talk First). In TTF fashion, the tag transmits first
information contained in the chip to the interrogator. The data /
Event Handler consists of two parts, the Request Handler and the
Data processing. The request Handler handles events (RFID
reader or user request) and transfers the message to the Data
processing unit that is responsible for processing. “The main
tasks of this unit are: 1) determine the request type; 2) extract
data in the envelope; 3) verify data formats and consistency and
4) record data in the shared database. After that, the notification
service is automatically called to inform intended
users.”(Gnimpieba et al. 2015)

„Software systems are used to support the warehousing
processes. Starting as Inventory Control Systems, todays WMS
contain much more functionality and optimisation routines.
Order picking as the process of retrieving products from storage
in response to a specific customer request is considered as a core
function within a WMS. “

(Moellera, 2011)

“

Experiences from

practice show that about a half of the total operating expenses of

a warehouse is spent by order picking. “ (Tompkins et al. 2013)

or presents a process of gathering raw materials or products
which are prepared according to some customer orders (Reif et
al. 2010).

3 Methodology and data

The main aim of the paper is to identify the impact of selected
information technologies on selected logistics processes.
According to Commission Regulation EU no. 651/2014
distinguishes micro enterprises, small enterprises, medium-sized
enterprises and large enterprises. The object of the research,
which was conducted by questionnaire survey were small,
medium-sized and large enterprises operating in the Slovak
Republic.

Table 1: Definition of enterprises into micro, small, medium-
sized and large enterprises

Enterprises

Staff headcount

Turnover

Balance sheet

total

Micro

enterprises

< 10

≤ € 2 million

Small

enterprises

< 50

≤ € 10 million

Medium-sized

enterprises

< 250

≤ € 50 million

≤ € 43 million

Large

enterprises

> 250

> € 50 million

> € 43 million

Source: EUR-Lex. Commission Regulation (EU) No 651/2014.
[online]. 2014. [viewed 2018-11-10]. Available from: <http://eur-
lex.europa.eu/legal-content/SK/TXT/?uri=CELEX:32014R0651>

The survey was attended by 85 Slovak enterprises. Of the
participating enterprises, 34.12% were from the automotive
industry, 22.35% from the engineering industry, 16.47% from
the electrotechnical industry, 10.59% from the food industry,
5.88% from the construction industry, 4.71% from the textile
industry, 3.53% from the chemical industry and 2.35% from the
wood processing industry.

In order to achieve the main objective of the paper, we have used
several scientific methods.

From the standard classical scientific

methods we used: the method of literary research, the method of
analysis and synthesis, the method of induction and deduction,
the method of comparison, the method of scientific abstraction.
From specific special methods, we applied a combination of
inquiry methods, classification method, mathematical-statistical
methods to quantify and quantify survey results. When asked
respondents to determine the level of consent to claim, the Likert
scale was used on a scale of 0 to 6 (where 0 - I disagree to 6 - I
agree).

From the statistical tests, Pearson's Chi-square (

) goodness of

fit test was used. This test is included to tests of goodness-of-fit,
which provide which allow to test null hypothesis H

, on

previously selected level of importance

α that random selection

was performed as division of given type, or unknown parameters
against alternative hypothesis H

, that does not come from this

division (Ostertagová, 2012).

On the basis of the main objective of paper was determined and
tested following hypothesis:

H

: There is no statistically significant dependence on the

significance level of

α = 0,05 between the improvement of

logistics processes and usage of Warehouse Management
System (WMS).
H

: There is a statistically significant dependence on the

significance level of

α = 0,05 between the improvement of

logistics processes and usage of Warehouse Management
System (WMS).

Calculated testing characteristics (Chi-square = 12.229) was
compared with 95 percentile

– division with (r – 1)

⋅ (s – 1) =

(3 – 1)

⋅ (3 – 1) = 4 degree of freedom χ

0,95

(4) = 9,487729.

Based on the hypothesis testing, we conclude that there is a
statistically significant dependence between the improvement of

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