KNOWCON_2025_Knowledge_on_Economics_and_Management._Conference_Proceedings_Muller_Michal

KNOWCON 2025 Knowledge on Economics and Management

KNOWCON 2025 Knowledge on Economics and Management

Conference Proceedings

The conference took place on December 4–5, 2025 under the auspices of Assoc. Prof. Mgr Jan Stejskal, M.A., Ph D., Dean of the Faculty of Arts, Palacký University Olomouc.

This conference proceedings contains single-blind peer-reviewed papers. Authors are responsible for the content and accuracy of their papers.

Edited by:

Mgr. Michal Müller, Ph.D. et Ph.D.

Scientific Committee:

Prof. Kai Hockerts, Ph.D. (Copenhagen Business School)

Prof. Pasi Luukka (President of NSAIS; LUT School of Business and Management)

Prof. Heli C. Wang (Singapore Management University)

Assoc. Prof. Anita Atanasova, Ph.D. (University of Economics Varna)

Assoc. Prof. Ing. Jaroslava Kubátová, Ph.D. (Palacký University Olomouc)

Assoc. Prof. Dr. Raphael Lissillour, Ph.D., (IPAG Business School Paris)

Assoc. Prof. Ing. Ludmila Mládková, Ph.D. (University of Economics, Prague)

Assoc. Prof. Mgr. Pavla Slavíčková, Ph.D., (Palacký University Olomouc)

Assoc. Prof. Radoslaw Walczak, Ph.D. (Opole University, Institute of Psychology)

Assoc. Prof. Ing. Jarmila Zimmermanová, Ph.D., (Palacký University Olomouc)

Dr. Echo Liang Shang, (The Education University of Hong Kong)

www.knowledgeconference.upol.cz

First Edition

This work is licensed under a Creative Commons BY-SA license (Attribution – ShareAlike).

The license terms can be found at https://creativecommons.org/licenses/by-sa/4.0/

Editor ©Michal Müller, 2025

©Palacký University Olomouc, 2025

DOI: https://doi org/10.5507/ff.25.24467023

ISBN 978-80-244-6702-3 (online: iPDF)

Contents

Hassan Amjad and Jan Stoklasa: Thenature of the evaluation method matters.Onthe importance of “relative- vs. absolute-type”methodchoiceinassessingtheeffect oftourismonUNESCOnatural heritagesites ..............................................................................................................................5

Ján Holý and Vladimír Bolek: Structure,Agency,andtheRecursivenessofSocialPractices:A StructurationTheory Perspective on Organizational Resilience and Crisis Adaptation ......................12

Kalin Kalev: TheneedofAIinterpretationofaccountingdata 19

Jozef Kovács and Ivana Mišúnová Hudáková: Durationofdevelopmentandbusinesspotentialof innovations:Empiricalfindings from business practice 26

Jaroslava Kubátová, David Kosina, Ondřej Kročil, Michal Müller and Pavla Slavíčková: Soft SkillsasCivicSkills:Rethinking21st-CenturySkillsFrameworks.........................................................33

Katarzyna Łukaniszyn-Domaszewska, Katarzyna Mazur-Włodarczyk and Elżbieta Karaś: InstitutionalengagementintheadvancementofPolish-Czechcooperationand shared cultural heritage management.............................................................................................................................40

Ludmila Mládková: SpiritualKnowledgeManagement–ManagingUnmanageable 47

Michal Müller: KnowledgeWorkers’PerceptionsofGenerativeAIandtheErosionofHumanSkills 54

Dana Ondrušková: From Protection to Participation: Economic Integration of Ukrainian Refugees in Central Europe ......................................................................................................61

Katarína Procházková: GreenInnovationsintheAgeofBigData:ABibliometricStudytoGuideFuture Research. ..................................................................................................................................67

Patrik Richnák: ShapingtheFutureofSustainableTransport:TheRoleof UniversityStudentsinthe StudyFieldofEconomicsandManagementintheAdoptionofElectromobility 74

Vitin Sawant and Jana Blštáková: Measuringthe Impact ofDigitalHRMPracticesonOperational Efficiency: Systematic Literature Review. 81

Alexander Šarlina and Ivana Mišúnová Hudáková: InnovationActivityofCompaniesasaToolof StrategicManagement................................................................................................................88

Zsuzsanna Tóth, Erika Seres Huszárik, Mohamad-Noor Salehhuddin Sharipudin and Suffian Hadi Ayub: TheImpact ofCultureontheDevelopment ofBusinessRelationships 95

The nature of the evaluation method matters. On the importance of “relative- vs. absolute-type”method choice in assessingthe effect oftourism on UNESCOnatural heritage sites

Hassan Amjad1* , Jan Stoklasa2,1

1LUT University, Business School, Yliopistonkatu 34, 53850 Lappeenranta, Finland

2Palacký University Olomouc, Faculty of Arts, Department of Economic and Managerial Studies, Křížkovského 8, 779 00, Olomouc, Czech Republic

Abstract: When the ranking of alternatives is the main objective of a decision-support model, it is usually one of the wide family of relative-type evaluation methods that is chosen to be applied. These methods are designed to provide ranking. However, they also derive the evaluations of the alternatives, and thus also their corresponding ranking, from comparisons with other alternatives or with benchmarks based on the set of alternatives. As such the (often implicit) assumption of the set of alternatives being final is crucial. However, in many cases the set ofalternatives is tosomeextent arbitrary, composed ofthealternatives for which theneeded criteria values are currently available etc. In the recent turbulent times, it is also the variability and instability of the whole decision-making environment that can make some alternatives unavailable, introduce new alternatives,orotherwise influencethe composition ofset ofalternatives. In thispaperweshowhow theranking of selected UNESCO natural heritage sites based on tourism-related risk derived by a relative-type method (VIKOR) depends on the alternatives being evaluated. We discuss the rank-reversal effect connected with changes inthesetof alternatives andits implications ontherobustness andmanagerialusefulness oftheoutputs derivedbysuchadecision support. Inshort, weshowthat thechoice of thetype of method (relative vs.absolute) matters, and that, if made incorrectly, it can render the results useless or difficult to interpret.

Keywords: VIKOR,evaluation, absolute,relative, tourism,risk

JEL classification: D81 L83 C44

1. Introduction

In decision-support systems where the primary goal is to rank the alternatives within a given set (i.e. alternatives that are being considered), relative-type evaluation methods are frequently employed. These methods, including well-established ones such as VIKOR, derive rankings not by assessing each alternative in isolation, but by comparing them either directly with one another or against composite benchmarks created from the set of considered alternatives itself. While effective in producing rankings, this approach inherently relies on a crucial though often overlooked assumption: that the set of alternatives under evaluation is complete, fixed, and representative. However, in real-world scenarios, particularly those characterized by dynamic conditions, this assumption rarely holds true. The composition of the set of alternatives may be influenced by data availability, contextual constraints, cognitive and behavioral constraints on the decision-maker side (related to the set of alternatives being considered), or rapidly changing environments, all of which introduce a level of instability into the decision-making process when relative-type evaluation methods are being used. This can significantly affect the stability and thus reliability of the outcomes generated by relative-type methods. One important consequence of this dependency is the rank-reversal effect where the

* Corresponding author’s email: hassan.amjad@student.lut.fi

introduction or removal of alternatives leads to, potentially unexpected and difficult to anticipate, changes in the ranking of the remaining options. This phenomenon raises critical questions about the robustness and interpretability of the outputs of such models, especially when used for informing policy or strategic decisions in variable contexts – particularly if the set of alternatives is expected to change or when the set of alternatives has been chosen arbitrarily e.g. as a subset of a much larger alternatives set. In this case the ranking can be influenced by the arbitrary reference set choice.

In this paper, we outline these concerns by examining a real-life case study involving the ranking of selected UNESCO natural heritage sites based on tourism-related risk (Selcuk et al., 2023) and show the potential adverse effect of relative-type evaluation. Using the VIKOR method as a representative of the relative-type methods family, we demonstrate how sensitive the resulting rankings are to the content of the set of alternatives considered. Our findings underscore the importance of method selection, particularly the choice between relative- and absolute-type evaluation approaches and highlight the potential pitfalls of applying relative methods in contexts where the stability of the alternative set cannot be assured.

2. Methodology

The objective of this paper is to demonstrate how rankings generated by a relative-type evaluation methods are sensitive to the composition of the set of alternatives and what real-life consequences this can have in decision-support. In line with Selcuk et al. (2023) we take the VIKOR method as a representative of relative-type multi-criteria decision-making (MCDM) methods and show how the rankings of alternatives suggested by VIKOR are affected by removals of alternatives from the set of alternatives. More specifically we identify and comment on pairwise rank reversals stemming from removals of a single alternative. This is done iteratively, so all �� 1 element subsets of an �� element original set of alternatives are investigated. After each removal the rankings of the remaining alternatives obtained by VIKOR are stored and analyzed and pairwise ranking changes are outlined.

2.1. Overview of the VIKOR Method

The VIKOR method was developed by Opricovic and Tzeng (2004) to determine a compromise solution for problems involving conflicting criteria. It evaluates each alternative relative to the best and worst performance observed among all alternatives in the current decision set. This inherently relative nature makes VIKOR susceptible to shifts in rankings when alternatives are added or removed. Here are the steps of the VIKOR method as suggested by Opricovic and Tzeng.

where calculating utility and regret measures in step 3, normalize the performance scores between 0 and 1 by expressing them as relative distances from the PIS, scaled to the range between the PIS and NIS:

Step 3

where where

criterion.

Step where

The parameter ν is introduced as the weight of the strategy of "the majority of attributes". Its value lies between 0 and 1. For specific choices of the value of �� we have specific interpretations:

ν=1 is maximizing group utility,

ν=0 means minimum individual regret strategy,

ν=0.5 is a compromise, usually preferred, approach between the two previously mentioned.

Step 5: Rank the alternatives based on the values of ����,���� and ���� First arrange the alternatives in ascending order, according to the values of ��,��,and ��. This provides three ranking lists. We can conclude that ��′ is the best alternative, if two conditions are satisfied. Firstly:

where a ′ is the compromise solution with minimum �� value and a ′′ is the second-best alternative. However, the above-mentioned condition is not enough on its own. For alternative a ′ to be considered the best, it must have a significant enough difference in its �� value compared to the second-best alternative and the difference must be greater than or equal to a threshold called ����, which is calculated as:

where �� is the total number of alternatives. And secondly a ′ should not only be the best choice based on Q, but it should also outperform the other alternatives in �� or ��

2.2. Limitations of Relative Evaluation

Rank reversal in the VIKOR method arises primarily from the sensitivity of certain computational steps to the composition of the set of alternatives. The most critical step contributing to this phenomenon is Step 2, where the best and worst values for each criterion are determined based on all available alternatives. When an alternative is removed, these extreme values may change, even if the actual performance of the remaining alternatives remains the same. This leads to a recalibration of the normalized performance matrix, thereby altering the subsequent calculations. In Step 3, the aggregated group utility (����) and individual regret (����) are computed using the normalized values. Since these are directly influenced by the best and worst criterion values from Step 2, any changes there affect all alternatives scores. In Step 4, the VIKOR index (����) is calculated by combining (����) and (����) and then scaling them based on the minimum and maximum values across the set. Removal or addition of an alternative can change these min/max values, which in turn affects the scaling and final rankings.

Table 1: Description of Alternatives, adapted from Selcuk et al. (2023)

Alternative Site Name

A1

Atlantic Forest Southeast Reserves (Brazil)

A2 Białowieża Forest (Belarus, Poland)

A3 Brazilian Atlantic Islands (Brazil)

A4 Forest Complex of Dong Phayayen-Khao Yai (Thailand)

A5 Durmitor National Park (Montenegro)

A6 Galápagos Islands (Ecuador)

A7 Gondwana Rainforests of Australia (Australia)

A8 Greater Blue Mountains Area (Australia)

A9 Historic Sanctuary of Machu Picchu (Peru)

A10 Hyrcanian Forests (Iran)

A11 Kenya Lake System in the Great Rift Valley (Kenya)

A12 Komodo National Park (Indonesia)

A13 Lake Baikal (Russian Federation)

A14 Lake Malawi National Park (Malawi)

A15 Mana Pools National Park (Zimbabwe)

A16 Cultural and Natural Heritage of the Ohrid Region (Albania)

A17 National Park of Phong Nha-Ke Bang (Viet Nam)

A18 Rainforest of the Atsinanana (Madagascar)

A19 Sagarmatha National Park (Nepal)

A20 Serengeti National Park (Tanzania)

A21 Sinharaja Forest Reserve (Sri Lanka)

A22 Vredefort Dome (South Africa)

A23 Western Caucasus (Russian Federation)

A24 Western Ghats (India)

In VIKOR and other relative-type approaches, alternatives are evaluated in comparison to each other rather than against fixed, external benchmarks. Consequently, the outcome depends heavily on the composition of the alternatives set. If alternatives are added or removed, the reference points shift, potentially altering the entire ranking outcome. If the set of alternatives is chosen arbitrarily, then the reference points and the corresponding ranking of alternatives can be arbitrary too. While the relativetype evaluation structure may appear to reflect interactions among alternatives, it introduces significant instability when the set is not finalized (note that stability of the set of alternatives is a crucial assumption of all relative-type methods, even though it is not frequently explicitly stated). Thus,

the evaluation method chosen relative or absolute significantly influences how robust and dependable the decision-making process will be. Some issues with relative type methods have been identified recently by Amjad and Stoklasa (2025). Their paper argues that relative-type methods inherently carry a risk of rank reversal, and it needs to be further quantified through the development of rank reversal indices. In contrast, absolute-type methods, by their design, use stable reference points that are not affected by the presence or absence of some alternatives, leading to pair-wise stable rankings. This distinction underscores the importance of understanding the nature of evaluation when choosing a method, particularly in decision-making contexts where stability and reliability are critical.

3. Case Study: Re-Examining Tourism Risk Rankings in UNESCO Natural Heritage Sites

To demonstrate the risks and limitations associated with relative-type evaluation methods, particularly the rank-reversal phenomenon, this study builds upon an existing multi-criteria decision-making (MCDM) analysis conducted by Selcuk et al. (2023). In their paper, the authors assessed tourismrelated threat levels for 24 UNESCO natural heritage sites with twelve different criteria shown in table 1 and table 2 respectively by using a combination of MCDM techniques ultimately identifying which sites are the most endangered ones. The original authors aim to determine the effects and threat levels of tourism in World Natural Heritage Sites by identifying top 3 most risky sites and used three individual methods and aggregated their outputs using a fourth method, aiming to ensure robustness and objectivity. In our case study, we use their results as a baseline and apply the VIKOR method under different compositions of the set of alternatives to analyze how sensitive the pairwise rankings are to changes in the set of evaluated alternatives. Specifically, we replicate their setting but iteratively remove a single alternative from the original set of alternatives and then observe how the rankings shift.

Table 2: Definition of Criteria (Selcuk et al., 2023)

Code Criterion name

C1 Property

C2 Date of Inscription

Definition

Size of the area in hectares

How many years have it been on the UNESCO heritage list?

C3 Assistance Total donations and assistances for the site (USD dollar)

C4 Reporting Trend Point Score showing the danger level of the area received in the evaluation report submitted to UNESCO

C5 Biodiversity Fauna Number of fauna species living in the area

C6 Biodiversity Flora Number of flora species living in the area

C7 Number of visitors The current number of people who visited the site recently

C8 Accommodation The number of accommodation facilities is within 50 km of the area

C9 Impact of tourism Level of assessment of tourism impact included in the UNESCO conservation report

C10 Infrastructure in the buffer zones

C11 Overall assessment for threats

C12 Tourism and visitation management

Level of assessment of the impact of tourism on infrastructure in the UNESCO conservation report

Overall assessment level of threats in the UNESCO conservation report

The level of assessment of the tourism and visitation management status of the area included in the UNESCO conservation report

4. Results

The analysis revealed significant sensitivity in the VIKOR-generated rankings when a single alternative was removed from the evaluation set. In all 24 exclusion scenarios, rank changes occurred, demonstrating the non-robust nature of the method. Particularly notable were rank reversals affecting the top-tier alternatives, those deemed most at risk. For example, the removal of the Kenya Lake System resulted in a re-ranking that affected globally recognized sites such as Machu Picchu (A9), which shifted in relative position despite no change in its input data (under some compositions of the set of alternatives, it is among the top three sites most at risk, under some it is not among to top three). These findings are clearly illustrated in Table 3, which presents the original ranking of the 24 UNESCO natural heritage sites (denoted as A1 through A24 and summarized in the first column) alongside the rankings generated under each exclusion scenario (alternatives excluded from the original set of alternatives are presented in the top row in Table 3, the ranking of the remaining ones from most at risk to the least at risk constitutes the rest of the respective column). The table highlights the frequency and magnitude of rank changes, including shifts in the top three and bottom three positions. Instances of rank reversal where the relative order between two alternatives changes are widespread, with several sites experiencing multiple reversals across different scenarios.

Table 3: Rank Reversal in Relative Type Evaluation (VIKOR) by Removing Alternatives

This ranking instability is not a reflection of underlying changes in site conditions or data but a direct consequence of the relative nature of the method. As VIKOR benchmarks against the current set's best and worst, changes to the set alter reference points and computed solutions. For an absolute-type method the pairwise rankings would not be changing at all, as they rely on fixed, external benchmarks. Therefore, we do not present a side-by-side comparison with an absolute method, as its leave-one-out exercise would trivially show no change in ranking, offering no further insight into the instability demonstrated here.