<figure><img src="image_21.png" /><figcaption>Figure 1 Research model</figcaption></figure>

**Method** – A time-lagged survey has been conducted on a multisource sample of 167 unit managers and their 376 employees from 90 Croatian organizations. Managers retrospectively assessed team/unit characteristics (unit ambidexterity, team cross-training, and team job design happiness) at Time 1. In addition, they provided supervisor-perspective ratings (Carlson et al., 2011) of team performance at Time 2. On the other hand, employees retrospectively assessed the paradoxical leadership of their immediate supervisor and shared their perception of team cohesion, both at Time 1. Employee responses were aggregated at the unit level, thus enabling us to proceed with a single (unit)-level analysis. Four methodological approaches were taken to assure the robustness of our results: (1) mediation analyses using PROCESS macro for SPSS (Hayes, 2018); (2) mediation analysis using partial least squares structural equation modeling (PLS-SEM); (3) necessary condition analysis (NCA; Dul, 2016); and (4) combined use of PLS-SEM and NCA (Richter et al., 2020).

**Findings** – We found consistent evidence across different data analysis techniques applied. Team job design happiness (TJDHAPP) mediates the relationship between team antecedents and team outcome, indicating the sufficiency of paradoxical leadership, unit ambidexterity, team cohesion, and team cross-training for TJDHAPP, as well as the sufficiency of TJDHAPP for team performance. Moreover, unit exploration, together with team cross-training, were recognized as necessary conditions (that is, prerequisites or critical success factors) for the occurrence of both the mediator (TJDHAPP) and outcome (team performance) variables.

**Theoretical contribution** – This research primarily contributes to team effectiveness and job design literature by highlighting the importance and intervening role of team job design happiness for achieving high team performance. Additionally, the results are valuable to human resource management (HRM) and organizational paradox scholars interested in further studying cross-training and paradoxical leadership style as viable antecedents of various organizational and work phenomena, including behavior and performance.

**Practical implications** – To be successful, managers should consider what makes their employees happy and satisfied with job design at the unit level. Besides acquiring a paradoxical leadership style and designing ambidextrous work unit tasks, they should also introduce cross-training practices and create team cohesion. Although these leadership, HRM, unit- and job design features significantly contribute to team performance, unit ambidexterity and team cross-training are critical and, thus, should be introduced beforehand.

**Keywords** – paradoxical leadership, unit ambidexterity, team cross-training, team cohesion, team job design happiness, team performance, method triangulation
REFERENCES

1. Bell, S. T. (2007). Deep-level composition variables as predictors of team performance: A meta-analysis. *Journal of Applied Psychology, 92*(3), 595-615.

2. Carlson, E. N., Vazire, S., & Furr, R. M. (2011). Meta-insight: Do people really know how others see them? *Journal of Personality and Social Psychology, 101*(4), 831-846.

3. D'Innocenzo, L., Mathieu, J. E., & Kukenberger, M. R. (2016). A meta-analysis of different forms of shared leadership-team performance relations. *Journal of Management, 42*(7), 1964-1991.

4. Dul, J. (2016). Necessary Condition Analysis (NCA): Logic and Methodology of "Necessary but not Sufficient" Causality. *Organizational Research Methods, 19*(1), 10-52.

5. Dutschke, G., Jacobsohn, L., Dias, A., & Combadao, J. (2019). The job design happiness scale (JDHS). *Journal of Organizational Change Management, 32*(7), 709-724.

6. Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-based Approach. New York: The Guilford Press.

7. Mathieu, J. E., Gallagher, P. T., Domingo, M. A., & Klock, E. A. (2019). Embracing Complexity: Reviewing the Past Decade of Team Effectiveness Research. *Annual Review of Organizational Psychology and Organizational Behavior, 6*, 17-46.

8. Richter, N. F., Schubring, S., Hauff, S., Ringle, C. M., & Sarstedt, M. (2020). When predictors of outcomes are necessary: guidelines for the combined use of PLS-SEM and NCA. *Industrial Management & Data, 120*(12), 2243-2267.

9. Volpe, C. E., Cannon-Bowers, J. A., Salas, E., & Spector, P. E. (1996). The impact of cross-training on team functioning: An empirical investigation. *Human Factors: The Journal of the Human Factors and Ergonomics Society, 38*(1), 87-100.

10. Zhang, Y., Waldman, D. A., Han, Y. L., & Li, X. B. (2015). Paradoxical leader behaviors in people management: antecedents and consequences. *Academy of Management Journal, 58*(2), 538-566.
Vlahović Olivera

University of Montenegro, Faculty of Tourism and Hotel Management

Nebojša Janićijević

University of Belgrade, Faculty of Economics

Job satisfaction is an individual's attitude towards work that encompasses cognitive, affective, and evaluative reactions to the job (Luthans 2005). Job satisfaction is a complex attitude because it arises from the employee's appraisal of multiple work dimensions made on a daily basis (Kinicki et al. 2002). An individual's job satisfaction is based on the extent to which the job provides rewards or outcomes that the individual considers important (Locke, 1969). The importance and popularity of the job satisfaction concept stems from its presumed positive impact on employee productivity (Judge et al. 2001).

To date, a number of factors affecting job satisfaction at both the organizational and individual level have been identified (Janićijević, et al., 2015; Luthans 2005). In several works so far has been shown that organizational culture must be included in the organizational factors influencing job satisfaction (Janićijević et al., 2018; Lund 2003; Silverthorne 2004; Johnson & McIntyre 1998). The aim of this paper is to show that changing the organizational culture also changes the level of job satisfaction of employees, which proves that organizational culture is a factor in job satisfaction.

Research into the impact of organizational culture change on job satisfaction was conducted empirically as part of a wider research into the transition of the hotel sector in Montenegro. Changes in organizational culture and employee satisfaction in hotel companies in Montenegro were investigated on a sample of 765 employees in 47 hotels, during a period of 5 years. The OCAI questionnaire developed by Cameron and Quinn within the Competing voices framework (Cameron, Quinn, 1999) was used to measure organizational culture changes. This questionnaire is based on the classification of organizational cultures that recognizes 4 types of organizational culture: clan, hierarchy, market and adhocracy. Changes in the organizational culture were followed by changings in the dominant type of culture in the selected hotels during a five-year period. To measure job satisfaction, a questionnaire developed in earlier research on job satisfaction in Serbia (Janićijević, et al., 2015; Kovačević, Petrović, 2006) was used, and it consisted of 15 job dimensions. Respondents rated their satisfaction with those job dimensions at the beginning and at the end of the research period.

The research was carried out in the context of the transition of the hotel sector in Montenegro, whose main characteristics were tender privatization and the entry of foreign capital. This led to a departure from the previous way of operating hotels inherited from socialist times and the acceptance of modern hotel organization and its functioning. The consequence of such a transition is the comprehensive transformation of hotels in Montenegro, which was also reflected in the organizational culture in those hotels.
The research results showed that during the five-year transition of the hotel sector, the organizational culture of hotel companies changed significantly. The dominant trend of changes was the transformation of the culture of the clan into a culture of hierarchy. Namely, at the beginning of the transition, clan culture was dominant in 39 and hierarchy culture in 4 out of 47 hotels in the sample. At the end of the period, however, out of 47 hotels, clan culture dominated in 20 hotels and hierarchy culture in 26 hotels. Even at 22 hotels, the culture of the clan was directly replaced by the culture of hierarchy. This changes of organizational culture in hotels in Montenegro were the result of the way in which the transition in this industry took place.

Confirmation of the hypothesis that organizational culture affects employee satisfaction can be obtained if we follow the changes in employee satisfaction in those hotels where the culture of the clan has been transformed into a culture of hierarchy and compare them with the satisfaction of employees in those hotels where the culture of the clan has remained dominant. The results of the research show that the overall level of employee satisfaction in 22 hotels where the clan culture was replaced by the culture of hierarchy decreased so that the average employee satisfaction rating fell from 3,96 to 3,02 over a five-year period. On the other hand, the average rating of satisfaction of employees in hotels where clan culture remained dominant has not significantly changed because 5 years ago it was 3,99 and now it's 3,89 Therefore, we conclude that the change of clan culture to hierarchy culture caused a decline in employee job satisfaction. This result is expected considering some earlier research (Janićijević, et al, 2018). The culture of hierarchy, as a culture typical of a bureaucratic type of organization, generates a lower level of employee satisfaction because the organization is viewed through the metaphor of a machine, and the orientation towards people and their needs is very low. On the contrary, in the culture of the clan, in which the metaphor for the organization is the family, orientation to people and their needs is very high, so employee satisfaction is also higher. This is especially important in the context of the Montenegrin national culture, which is characterized by extremely high collectivism (Hofstede, 2024). It is interesting that with all the investigated job dimensions, there is a drop in satisfaction at transition from a clan culture to a hierarchy culture, except for two dimensions: salary and benefits. It is obvious that the transition of the hotel sector in Montenegro gave economic results, which was reflected in the increase in wages and improved benefits, so the satisfaction with those aspects of the job is also higher. However, all other very important dimensions of work, record a decline in employee satisfaction, so overall job satisfaction is also lower.

The theoretical contribution of the work consists in confirming the hypothesis that organizational culture is a significant factor in job satisfaction and that people-oriented cultures, such as clan culture, generate a higher level of employee satisfaction than task-oriented cultures, such as hierarchy culture. The practical contribution of the work consists in recommending hotel management in Montenegro to focus more on employee satisfaction, since only increasing salaries and benefits will not lead to an increase in that satisfaction.

Key Words: organizational culture, job satisfaction, Montenegro, hotel industry, transition
References

1. Cameron, K. S., & Quinn, R. E. (1999). *Diagnosing and Changing Organizational Culture*. Reading, MA: Addison-Wesley

2. Hofstede insights, https://www.hofstede-insights.com/country-comparison/ (Accessed January 25th, 2024)

3. Janićijević, N., Nikčević, G., & Vasić, V. (2018). The influence of organizational culture on job satisfaction, *Economic Annals*, 63(219), 83–114.

4. Janićijević, N., Kovačević, P., & Petrović, I. (2015). Identifying organizational factors of job satisfaction. *Economic Annals*, 60(205), 73-104.

6. Johnson, J. J., & McIntyre, C. L. (1998). organizational culture and climate correlates of job satisfaction. *Psychological Reports*, 82 (3), pp.843–850.

7. Judge T.A., Thorensen C.J., Bono J.E. & Patton G.K. (2001) The job satisfaction – job performance relationship: A qualitative and quantitative review. *Psychological Bulletin*, 127 (3), 376–407.

8. Kinicki A. J., Schriesheim C. A., McKee-Ryan F. M., & Carson K. P. (2002). Assessing construct validity of the job descriptive index: Review and meta-analysis. *Journal of Applied Psychology*, 87(1), 14-32.

9. Kovačević, P. & Petrović, I. (2006). Managers' job satisfaction: Construct validation, in B. Cerović, Ed. *Privatisation in Serbia: Evidence and analyses*, Beograd: CID Faculty of Economics, pp. 287-304.

10. Locke, E.A. (1969). What is job satisfaction? *Organizational Behaviour and Human Performance*, 4 (4), pp.309–336.

11. Lund, D. B. (2003). Organizational culture and job satisfaction. *Journal of Business & Industrial Marketing*, 18 (3), 219–236

12. Silverthorne, C. (2004). The impact of organizational culture and person-organization fit on organizational commitment and job satisfaction in Taiwan. *Leadership & Organization Development Journal*, 25 (7), 592–599.
# THE DIGITAL LEADERSHIP: HOW TO MEASURE?

**Karolina Kokot**

University of Zagreb, Faculty of Organization and Informatics, Croatia
[kkokot@foi.unizg.hr](mailto:kkokot@foi.unizg.hr)

**Marina Klačmer Čalopa**

University of Zagreb, Faculty of Organization and Informatics, Croatia
[marina.klacmer@foi.unizg.hr](mailto:marina.klacmer@foi.unizg.hr)

**Ivana Đundek**

University of Zagreb, Faculty of Organization and Informatics, Croatia
[idjundjek@foi.unizg.hr](mailto idjundjek@foi.unizg.hr)

**Theoretical background.** In the volatility, uncertainty, complexity, and ambiguity time (VUCA time), requirements from leaders have increased. The Environment of Industry 4.0 is unpredictable, and leaders must adapt their leadership style to fast changes and achieve agility. Technology is a rapidly changing and new technology are introduced daily. Digital leadership became one of the stream topics in the management field. Digital leadership is the result of leaders' awareness of new requirements or leaders can unknowingly adapt to new environments (push process) because of the digital transformation process.

Research questions are:

RQ1: How is representation of countries in this field?

RQ2: What is the most common topic in the digital leadership field?

RQ3: How to measure the level of digital leadership?

**Purpose of study and methods.** The aim of this paper is to explore present literature from 2015 and analyses exiting measurement scales for digital leadership. In this research paper methodology includes the quantitate and qualitative approach to answer on research questions. A literature review was done by bibliometric analysis in the Web of Science database. Bibliometric analysis included more than 150 papers and show this field's state of the art. Results of bibliometric analysis show the most relevant authors, most cited documents, and most representative countries. As part of bibliometric analysis, co-word analysis demonstrates the most frequent words and the trends topics to define recommendations for future research. Bibliometric analysis shows a lack of papers in this field and general countries underrepresentation.

**Findings.** Underrepresentation of papers in this field could lie in lack of methodology approach, like validated scale for measuring digital leadership. Exiting scales for measuring digital leadership in companies are analyses to define similarities and differences for scientists in this field. Results of existing empirical studies are also analyzed. The results of this analysis detect the advantages and disadvantages of the existing scales of digital leadership.

**Contribution.** The theoretical contribution of this paper lies in a critical and systematic review of existing theoretical and empirical findings in the domain of digital leadership. Also, results define the existing measurement scales for digital leadership to increase the new empirical studies in this field. Based on the analysis, recommendations related to digital leadership measures and potential paradoxes are presented in the conclusion.

**Key words:** digital leadership, methodology, bibliometric analysis
**Tomislav Baković**

Faculty of Economics and Business, University of Zagreb

**Domagoj Hruška**

Faculty of Economics and Business, University of Zagreb

**Lana Cindrić**

Faculty of Economics and Business, University of Zagreb

** presenting author

**Theoretical background** – While leadership literature abounds with descriptions of various functions, at its core, leadership primarily entails two essential tasks: articulating organizational goals, and motivating organizational agents to execute strategies aimed at achievement of these goals. In essence, leaders shape the character and trajectory of their organizations. Within this framework, the importance of learning from mistakes emerges as a critical aspect. Effective leaders not only set goals and motivate but also cultivate a culture that embraces failures as opportunities for learning and growth, thereby fostering resilience and continuous innovation within the organization.

For this topic, sensegiving emerges as a pivotal concept. Sensegiving refers to the deliberate efforts made by a leader to shape the collective interpretation of organizational events among its members, thereby promoting a preferred redefinition of organizational reality (Gioia and Chittipeddi 1991, Hodgkinson and Sparrow, 2002). Sensegiving represents pivotal processes for top management, particularly amidst failure, as this cognitive competency underpins behavioral effectiveness.

Individual interpretations and subsequent actions play a fundamental role in shaping and solidifying a shared understanding of the organization. This fusion of interpretation and action, described by Karl Weick as "organizational enactment" (Weick, 1979), underscores the notion that individuals actively contribute to the construction of their organizational environment. Central to this concept is the recognition of cognitive processes and behaviors in navigating the organizational landscape. The leader's interpretations not only shape their own reality but also contribute to the overarching organizational reality within which all decision-making occurs. Within this constructed reality, particularly significant is the concept of psychological safety, influencing how interpretations are shared, challenged, and ultimately integrated into the organizational fabric, thereby fostering a climate conducive to effective decision-making and organizational adaptation. This climate of psychological safety also nurtures affective organizational commitment, as individuals feel valued, respected, and supported in their endeavors within the organization, leading to a higher level of commitment to its goals and objectives.

Affective organizational commitment is defined as the intrinsic motivation of an organizational member to perceive the organization's task-related goals as ones they desire to fulfill rather than feeling obligated to fulfill them (Leroy et al., 2012). We argue that psychological safety serves as a mediating variable in relation between sensegiving and affective organizational
commitment, facilitating an environment where individuals feel secure in taking risks, expressing themselves, and admitting and learning from failures (Edmondson, 1999).

**Purpose of the study** – This study aims to explore the intricate relationship between leadership functions, organizational failure, sensegiving, psychological safety, and affective organizational commitment. By synthesizing existing theoretical frameworks and empirical evidence, we seek to elucidate how effective leadership practices, particularly in goal-setting, motivation, and sensegiving, can shape organizational responses to failure and cultivate a culture conducive to learning and resilience. Specifically, we investigate the mediating role of psychological safety in facilitating individuals' abilities to engage with failure, express themselves freely, and derive meaningful learning experiences from setbacks.

<figure><img src="image_22.png" /><figcaption>Figure 1 Research model</figcaption></figure>

**Method** – This article adopts a theory-building approach to investigate the interplay between leadership functions, organizational failure, sensegiving, psychological safety, and affective organizational commitment. Drawing from an extensive review of literature, we analyze key concepts and theoretical frameworks to construct a comprehensive understanding of the relationships among these variables. Through proposition development, we formulate hypotheses to elucidate how leadership functions influence sensegiving, how sensegiving affects psychological safety, and how psychological safety impacts affective organizational commitment. Subsequently, we develop a theoretical model visualizing these proposed relationships, providing a conceptual framework for further exploration and empirical testing. Finally, we synthesize findings from the literature review, conceptual analysis, propositions, and theoretical model to draw conclusions and offer implications for practice and future research in this domain.

**Findings** – By employing a theory-building approach to the topic, we anticipate several significant findings that will enrich our comprehension of leadership roles, organizational responses to failure, and the fostering of psychological safety and affective organizational commitment: (1) We predict that effective leadership functions, encompassing goal articulation and motivation, will positively correlate with organizational commitment in the face of failure. (2) We anticipate that psychological safety will play a crucial role in moderating the relationship between sensegiving and affective organizational commitment. Organizations with a climate of psychological safety are expected to exhibit higher levels of commitment among their members, particularly when individuals feel secure in expressing themselves and learning from failure
experiences. (3) Finally, we hypothesize that affective organizational commitment will be positively influenced by both sensegiving and psychological safety.

**Theoretical contribution** – This study contributes to the theoretical understanding of leadership dynamics by integrating concepts such as sensegiving, psychological safety, and affective organizational commitment into a cohesive framework. By exploring the interplay between these variables, we enhance existing theories on organizational resilience, learning from failure, and the role of leadership in shaping organizational culture. Our findings extend theoretical perspectives on sensemaking processes within organizations, particularly in relation to how leaders influence the interpretation of events and foster a climate conducive to learning and adaptation. Additionally, our examination of the mediating role of psychological safety provides valuable insights into the mechanisms through which leadership practices influence affective organizational commitment, enriching scholarly discourse on organizational behavior and effectiveness.

**Practical implications** – These expected findings have significant implications for organizational practice, highlighting the importance of leadership strategies that promote psychological safety and sensegiving. By nurturing a supportive environment where learning from failure is encouraged, organizations can enhance their resilience and commitment, ultimately fostering sustained success and growth.

**Keywords** – Leadership dynamics, Sensegiving, Psychological safety, Affective organizational commitment, Learning from failure

## REFERENCES

1. Cannon, M., & Edmondson, A.C. (2005). Failing to Learn and Learning to Fail (Intelligently): How Great Organizations Put Failure to Work to Innovate and Improve. Long Range Planning, 38, 299-319.

2. Carmeli, A., & Gittell, J.H. (2009). High-quality relationships, psychological safety, and learning from failures in work organizations. *Journal of Organizational Behavior, 30*, 709-729.

3. Carmeli, A., & Sheaffer, Z. (2008). How Learning Leadership and Organizational Learning from Failures Enhance Perceived Organizational Capacity to Adapt to the Task Environment. *The Journal of Applied Behavioral Science, 44*, 468 - 489.

4. Edmondson, A. C., 1999. Psychological Safety and Learning Behavior in Work Teams. *Administrative Science Quarterly*, 44(2), 350-383.

5. Gioia, Dennis A., and Kumar Chittipeddi. 1991. Sensemaking and Sensegiving in Strategic Change Initiation. *Strategic Management Journal*, 12:433-448.

6. Hodgkinson, Gerard, and Paul R. Sparrow. 2002. The Competent Organization. Buckingham: Open University Press.

7. Lattacher, W., & Wdowiak, M., (2020), Entrepreneurial learning from failure. A systematic review. *International Journal of Entrepreneurial Behavior & Research*. https://doi.org/10.1108/ijebr-02-2019-0085.

8. Leroy, H., Palanski, M. i Simons, T., 2012. Authentic Leadership and Behavioral Integrity as Drivers of Follower Commitment and Performance, *Journal of Business Ethics*, 107(3), 255-264.

9. Mtibaa, N., & Boudabbous, S., 2023. The Realities of Learning through Failure in Entrepreneurship: Results of Qualitative Research. *International Review of Management and Marketing*. https://doi.org/10.32479/irmm.14239.
10. Rhaiem, K., & Amara, N., (2021), Learning from innovation failures: a systematic review of the literature and research agenda. *Review of Managerial Science*, pp. 1-46. https://doi.org/10.1007/S11846-019-00339-2

11. Singh, S., Corner, P., & Pavlovich, K., 2007. Coping with entrepreneurial failure. *Journal of Management & Organization*, 13, pp. 331 - 344. https://doi.org/10.5172/jmo.2007.13.4.331

12. Weick, Karl E. 1979. The Social Psychology of Organizing. Reading MA: Addison-Wesley.
Andreja Jaklič and Iris Koleša*

Faculty of Social Sciences, University of Ljubljana, Slovenia

*Presenting and corresponding author (iris.kolesa@fdv.uni-lj.si)

**Extended abstract:** Distance is one of the central concepts in international business (IB). Despite receiving notable scholarly attention across different disciplines (see e.g. Beugelsdijk et al., 2018; Kirkman et al., 2006; Verbeke et al., 2017), managing various types of distance has remained one of the biggest challenges in IB practice. This is because distance exists across levels and affects organisations internally (e.g. by affecting employer attractiveness, staffing and human resources management practices; as well as other processes such as innovation) and externally (e.g. through different consumer preferences and business partner relations). The bigger the distance between social groups, such as nations, countries and markets, as well as their subparts, the greater the need for adaptation of companies' offering, their business practices and processes, as well as organisational structure and internal procedures.

As Zaheer et al. (2012) emphasise, international management is essentially the management of distance. Different aspects of distance have been used to explain the differences in IB strategies and operations across countries and regions (Beugelsdijk et al., 2018). Two of the most studied types of distance affecting IB have been psychic and cultural distance (e.g. Hofstede et al., 2010; Johanson and Vahlne, 2009). Although related, they operate on different levels of analysis, however. Psychic distance refers to the individual's perception of the differences between countries and is as such highly subjective and differentiated (also within in-groups), whereas cultural distance refers to the degree to which cultural values of two countries differ and is a county-level construct (Sousa and Bradley, 2006). We argue that understanding the two types of distance does not suffice for success in IB. This is due to a country-oriented view neglecting the complexity of international operation introduced by transnationalism and the existence of multi-ethnic states, which illustrate the importance of ethnic distance in IB. Ethnic distance is a social distance between different ethnic groups that derives from long-term acting ethnic stereotypes and prejudices (Rapti and Karaj, 2012). It also affects different aspects of business (including staffing and human resources management (Hosokawa, 1980)).

All three types of distance are inherently related to stereotypes; i.e. "/rather stable/ associations and beliefs about the characteristics and attributes of a group and its members that shape how people think about and respond to that group" (Dovidio et al., 2010, p. 8), whereby these beliefs and actions are based on (often subconscious) cognitive shortcuts or generalisations (Bargh, 1999; Hinton, 2000)). Stereotypes can have a significant effect on IB. However, their influence on different types of distance and the related implications for IB and management are not explicitly discussed in the literature. This is despite the fact that stereotypes are recognized as the building blocks of not only ethnic and other social groups' identities (see e.g. Kim and Loury, 2019) but also countries' image (Ingenhoff et al., 2020).

Although stereotypes oversimplify relations between countries or groups, overlook their subjective and context-specific nature, and do not pay enough attention to the mechanisms through which distance works (Shenkar, 2001), they still dominate various aspects of society, including IB. According to Hosokawa (1980) stereotypes perform several functions: (1) they maintain the status quo, (2) they create and maintain social roles, and (3) provide an occupational structure for determining job distribution, and contribute to dominant group solidarity. This can be damaging to the out-groups, however (e.g. by excluding their members from specific jobs or in the case of firms by excluding them from specific business relationships).
Negative stereotypes in particular are enhanced by geographic proximity – also due to closer economic, political, cultural and historic ties (Ingenhoff, 2020; Ültanır et al., 2016) and the related conflicts of interest stemming from competition (e.g. for jobs, business etc.). With digitalisation, (especially ethnic) stereotypes are on the rise. This is due to customization algorithms exposing people to like-minded messages (Lim, 2017). Crises are another important factor influencing the otherwise rather stable stereotypes (Alexander et al., 1999; Hosokawa, 1980; Jaklič & Svetličič, 2016; Udovič et al., 2017). A number of questions about the impact of stereotypes in IB are therefore (re)emerging.

In this conceptual paper, we address the following research questions: (1) How are psychic, ethnic and cultural distance related?<fnref n="1" /> (2) What is the impact of ethnic and country-related stereotypes on the three types of distance? (3) How are these relationships reflected in international business?

We review the growing body of literature to identify the (dis)advantages of stereotypes in IB and approaches for utilizing stereotypes to either diminish or enhance distance in a way that facilitates IB. Our literature review links paradox theory to social identity theory in addressing the multilevel in-group- out-group dynamics influenced by (ethnic and country-related) stereotypes and distance. This allows us to develop propositions on the relationships between the studied concepts and their implications for international business and management (in particular in terms of individuals' willingness to work for a business of a specific national origin, with colleagues of specific nationalities and in areas where particular nationalities dominate, which in turn also has implications for innovativeness and productivity; in addition, we take into account how stereotypes affect consumer behaviour as well as entity behaviour (especially in terms of international trade)).

We address paradoxes across all four categories defined by Smith and Lewis (2011), i.e.: (1) belonging as stereotyping is very much part of identity building and confirmation, (2) organizing as stereotyping also has implications in terms of collaboration and competition and routine and change within teams and organisations as a whole, (3) performing as stereotyping is reflected in the often conflicting demands of both internal and external stakeholders of an organisation (also intra-stakeholder group), and (4) learning as stereotyping implies building on traditions yet clashes in stereotypes can also result in change and innovation. We thereby focus on stereotypes in the Western Balkans as a region with multi-ethnic states and multiple identity clashes. The region is chosen as a case study due to it being marked by plurality and change (e.g. transition), likely to push latent paradoxical tensions to become salient (see also Smith and Lewis, 2011).

Besides theory building, our paper has important practical implications: it namely indicates how stereotypes can be utilized to enhance or diminish distance in order to facilitate collaboration, innovation and business, as well as what measures are needed to prevent them from fostering conflict, stagnation and protectionism.

**Keywords:** stereotypes, psychic distance, ethnic distance, cultural distance, Western Balkans, international business

<footnote n="1">¹ By considering various types of distance, we employ a multilevel approach to our theory building, which is consistent with the paradox theory's aim to uncover and explain tensions across levels of analysis (Smith and Lewis, 2011).</footnote>
References

1. Alexander, M. G., Brewer, M. B., & Hermann, R. K. (1999). Images and affect: A functional analysis of out-group stereotypes. *Journal of Personality and Social Psychology, 77*(1), 78–93. https://doi.org/10.1037/0022-3514.77.1.78

2. Bargh, J. A. (1999). The cognitive monster: The case against controllability of automatic stereotype effects. In S. Chaiken and Y. Trope (eds). *Dual Process Theories in Social Psychology* (pp. 361–382). New York: Guilford.

3. Beugelsdijk, S., Ambos, B. & Nell, P.C. (2018). Conceptualizing and measuring distance in international business research: Recurring questions and best practice guidelines. *Journal of International Business Studies, 49*, 1113–1137.
https://doi.org/10.1057/s41267-018-0182-4

4. Dovidio, J. F., Hewstone, M., Glick, P., & Esses, V. M. (2010). Prejudice, stereotyping and discrimination: Theoretical and empirical overview. In J. F. Dovidio, M. Hewstone, P. Glick, & V. M. Esses (Eds.). *The SAGE Handbook of Prejudice, Stereotyping and Discrimination* (pp. 3–29). https://doi.org/10.4135/9781446200919.n1

5. Hinton, P. R. (2000). *Stereotypes, Cognition and Culture*. Hove, UK: Psychology Press.

6. Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and organizations: software of the mind (3rd edition).

7. McGraw-Hill Professional.

8. Hosokawa, F. (1980). A functional theory of ethnic stereotypes. *Humboldt Journal of Social Relations, 7*(2), 15–30.

9. Ingenhoff, D., Segev, E., & Chariatte, J. (2020). The construction of country images and stereotypes: From public views to Google searches. *International Journal of Communication, 14*(2020), 92–113.

10. Jaklič, A & Svetličič, M. (2016). Do stereotypes hinder or promote foreign direct investment? The case of Western Balkan countries. *Teorija in praksa, 53* (5), 1095-1108.

11. Johanson, J. & Vahlne, J.-E. (2009). The Uppsala internationalization process model revisited: from liability of foreignness to liability of outsidership. *Journal of International Business Studies, 40*, 1411–1431.

12. Kim, Y.-C., & Loury, G. C. (2019). To be, or not to be: Stereotypes, identity choice and group inequality. *Journal of Public Economics, 174*, 36–52.
https://doi.org/10.1016/j.jpubeco.2019.01.009

13. Kirkman, B. L., Lowe, K. B., & Gibson, C. B. (2006). A quarter century of culture's consequences: A review of empirical research incorporating Hofstede's cultural values framework. *Journal of International Business Studies, 37*(3), 285–320.

14. Lim, M. (2017). Freedom to hate: Social media, algorithmic enclaves, and the rise of tribal nationalism in Indonesia. *Critical Asian Studies, 49*(3), 411–427.
https://doi.org/10.1080/14672715.2017.1341188

15. Rapti, E., & Karaj, T. (2012). Albanian university students' ethnic distance and stereotypes compared with other Balkan nations. *Problems of Education in the 21st Century, 48*, 127–134.

16. Shenkar, O. (2001). Cultural distance revisited: Towards a more rigorous conceptualization and measurement of cultural differences. *Journal of International Business Studies, 32*(3), 519–535.

17. Smith, W. K., & Lewis, M. W. (2011). Toward a Theory of Paradox: A Dynamic Equilibrium Model of Organizing. *The Academy of Management Review, 36*(2), 381–403.
http://www.jstor.org/stable/41318006
18. Sousa, C. M. P., & Bradley, F. (2006). *Cultural Distance and Psychic Distance: Two Peas in a Pod?* *Journal of International Marketing*. 14(1), 49–70.
[http://www.jstor.org/stable/25049037](http://www.jstor.org/stable/25049037)

19. Udovič, B., Jurše, M., Korez-Vide, R. Rašković, M., Svetličič, M., & Zupančič, R. (2017). Medkulturne razlike in stereotipi(zacija): prednost ali slabost pri političnem in gospodarskem sodelovanju med državami nekdanje Jugoslavije. Ljubljana: Fakulteta za družbene vede, Založba FDV.

20. Ültanır, G., Ültanır, E., & Irkörücü, A. (2016). A comparison of stereotypes of German and Turkish towards Balkans. *International Journal of Instruction, 9*(1):93-106.
DOI:10.12973/iji.2016.918a

21. Verbeke, A., van Tulder, R., & Puck, J. (2017). Distance in international business studies: Concept, cost and value. In A. Verbeke, J. Puck & R. v. Tulder (Eds.). *Distance in International Business: Concept, Cost and Value* (Progress in International Business Research, Vol. 12, pp. 17–43). Leeds: Emerald Publishing Limited.
[https://doi.org/10.1108/S1745-886220170000012016](https://doi.org/10.1108/S1745-886220170000012016)

22. Zaheer, S., Schomaker, M., & Nachum, L. (2012). Distance without direction: Restoring credibility to a much- loved construct. *Journal of International Business Studies, 43*, 18–27.
[https://doi.org/10.1057/jibs.2011.43](https://doi.org/10.1057/jibs.2011.43)
János Tóth

(Corvinus University of Budapest, PhD Student)
E-mail: janos.toth@uni-corvinus.hu

Ágnes Pető

E-mail: petoagnes9@gmail.com

Keywords: project management office; project management; project management maturity

The impact and importance of project management offices (from now on: PMOs) are inevitable and well researched. An effective and efficient PMO can increase the success rate achieved on projects, and as a result of this, the potential for gaining sustainable competitive advantage, and long term survival. However, the roles, and responsibilities, and especially the authority of PMOs are not in accordance with the expectations.

Although PMOs play a central role in organisations, most projects are implemented locally at the level of each organisational unit. This creates a paradoxical situation between the centralised PMO roles and decentralised, localised project implementation, i.e. the need for having a centralized and controlled overview of projects, and the expected flexibility generated on lower level. In order to reduce the potential tensions, PMOs keep some activities centralised, while others are left to the responsibility of the individual department.

A large body of literature confirms that a well-structured and managed project office can increase the number of successful projects in the organisation, it can increase organisational efficiency.

Nowadays, companies are facing the challenges of global markets, which are challenging them more than ever to maintain their market position and competitiveness. Furthermore, the impact of technological and innovation developments makes it necessary to harmonise strategic objectives. The development of a complex project management and project management office (PMO) with a holistic approach across all areas, which is a cornerstone of modern management, can provide a solution.

A project is essentially defined as a process with a defined activity, bounded, with a budget, created to achieve a specific goal (Project Management Institute, 2010), but which is aligned with the corporate strategy and operates as a temporary entity (Görög M, 2013). In the last decades, the discipline of project management has witnessed a major growth, driven by the pursuit of increasingly ambitious strategic goals within organisations, which has made the emergence of comprehensive project coordination inevitable in order to increase efficiency and achieve a high level of project success. Due to the information technology challenges, organisations can best respond by improving (i) project management capabilities, (ii) processes and (iii) governance structures (Singh et al. 2009). This creates opportunities for holistic project management activities, its presence at different levels of the organisation and its recognition as a business function. Increasing efficiency indicators and the achievement of strategic objectives through the successful implementation of projects by playing a high-level coordination role. In addition to the elements of the project triangle (time, cost and quality), emphasis is placed on stakeholder satisfaction, centralisation of functions and standardisation of project management practices (Cleland & Ireland, 2010).
The presence of a project office in an organisation is also an indicator of the development and maturity of the project maturity of that organisation. However, their emergence is highly correlated with the increase in the number and complexity of projects (Hobbs B, & Aubry M., 2006). Companies should strive to create an organisation that is responsible for and improves project management skills, thus contributing to more efficient operations, an effective solution to this is the project office (Meredith et. al. 2003). Standardizing project-based management processes, facilitating the sharing of resources, methodologies, tools and techniques, ensuring information flow, supporting project managers and project teams, identifying areas for improvement, improving project performance and meeting project schedules, and taking responsibility for the direct management of projects can all be part of the project office's responsibilities, if the organisation requires and its organisational structure allows (Project Management Institute, 2017; Aubry, Hobbs, & Thuillier, 2007). Despite its multifaceted nature and its involvement at different organizational levels, the project office does not represent a decision-making body (Cleland & Ireland, 2010). In its operations, the project office helps organizations achieve their strategic goals and links project management practices to the operation of corporate governance strategies and resource integration (Hubbard & Bolles, 2012; Bolles & Hubbard, 2015; Monteiro, Santos, & Varajao, 2016).

According to the results of a 2001 study (Block & Frame, 2001), offices are set up at the initiative of management within the company to establish standards and norms, to meet deadlines and to correct project management shortcomings. It is the responsibility of the organisation's manager to define the internal processes and inter-organisational relationships within the PMO (Harris, 2000). However, the question is whether the level of PMO to be established is (i) a supportive PMO, (ii) a controlling PMO or (iii) a directive PMO, is it most supportive of the organisation's development?

Thus, there is research gap regarding the tasks, i.e authors usually identify which tasks a PMO should perform. However, the level of centralisation is rarely considered. Thus my research which tasks and activities are centralised in each project office and which tasks are decentralised in each of the three different PMO levels in order to ensure smooth organisational functioning. The results are conducted based on the analysis of a leading Hungarian companies’ project management office, and semi-structured interviews with 10 PMO members from leading Hungarian companies (including the one mentioned before). As a result of this, a detailed set of activities and the level of centralisation is identified. The result is considered to be an exploratory research, and as a result of this, further analyses should be conducted in order to further reinforce the results.
References

1. Aubry, M., Hobbs, B., & Thuillier, D. (2007). A new framework for understanding organisational project management through the PMO., International Journal of Project Management, 328–336.

2. Block, T., & Frame, J. (2001). Today's Project Office: Gauging Attitudes. PM Network, 122-124.

3. Bolles, D., & Hubbard, D., (2015). PMO Framework and PMO Models for Project Business Management., PM World Journal, 1-22.

4. Cleland, D. I., & Ireland, L. R. (2010). Project Managers Portable Handbook., New York: McGraw Hill LLC.

5. Görög, M., (2003). A projektvezetés mestersége., Budapest: Aula Kiadó.

6. Harris, J., (2000, July 19). Theory of PMO Evolution. Retrieved from ProjectManagement.com: https://www.projectmanagement.com/articles/8415/theory-of-pmo-evolution#_ Download: 2024.02.10.

7. Hobbs, B., & Aubry M., (2006). Identifying the structure that underlies the extreme variety found among PMOs. Montreal: In: Proceedings of PMI research.

8. Hubbard, D., & Bolles, D., (2012). Executive PMO – Blending Project Management and Business Management - Second Edition., PM World Journal, 1-18.

9. Meredith, J., Shafer, S., & Mantel Jr. S., (2003). Project Management - A strategic Managerial Approach - Tenth Edition., Hoboken, NJ: John Wiley and Sons Inc.

10. Monteiro, A., Santos, V., & Varajao, J., (2016). Project Management Office Models - review., Procedia Computer Science 100, 1085 – 1094.

11. Project Management Institue., (2010). A guide to the Project Management Body of Knowledge., Pennsylvania: PMI Publicaions.

12. Project Management Institute., (2017). PMBOK Guide- A guide to the project management body of Knowledge - Sixth edition., Pennsylvania: Project Management Institute, Inc.

13. Singh, R., M. Keil, & V. Kasi., (2009). Identifying and overcoming the challenges of implementing a project management office., European Journal of Information Systems, 409.
Keywords: Project management, Generation, Soft skills, Competences

In an era characterized by globalization, acceleration, and rapid change, more organizations are adopting a project-based approach. Nieto-Rodriguez (2021) notes the escalating demand for projects in response to this trend. Despite the increasing importance of projects, a significant proportion of initiated projects end unsuccessfully, a trend particularly pronounced in the realm of information technology services (Agrawal and Thite, 2003). The Project Management Institute's (PMI) report in 2017 underscores the surge in demand for projects, accompanied by a corresponding increase in the need for project managers possessing the requisite competencies and skills. Competencies are crucial for project success, and numerous studies have emphasized the relationship between project success and the competencies of project managers (Blaskovics, 2014; Müller and Turner, 2007). Magano et al. (2020) and Voelkening (2014) suggest that project management skills may manifest differently for each generation, with strengths and weaknesses identified based on a specific skill set when examining each generation to maximize personal and project efficiency and success in the future.

Competencies can be categorized into hard and soft skills, with "hard" skills relating to technical knowledge and being explicit, specific, while "soft" skills are human-oriented, tacit, and transferable (Clarke, 2016; Dean, 2017; Jones et al., 2017). The emphasis on the human factor aligns with general labor market demands, drawing attention to the increasing role and value of soft skills, often referred to as "people skills" and emotional intelligence. It is widely acknowledged that there is a positive relationship between project success and project manager competencies. Goleman, Boyatzis, and McKee (2002) organize emotionally intelligent leadership competencies into four quadrants: self-awareness, self-management, social awareness, and relationship management.

The conceptual approach to generations has been explored by various disciplines, representing different views, but for research purposes, definitions from the fields of psychology and sociology are considered. Mannheim (1952) initially defined generations as individuals born in the same year, sharing a common place in the historical dimension of social processes. Strauss and Howe (1992), examining the history of the United States, describe the recurring cycles of age groups with distinct behavior patterns as "generations," stating that "a generation is a group of people who share a collective personality provided by the historical time and place they inhabit."

Generation Z, born between the mid-1990s and early 2010s, represents a unique cohort with distinct characteristics and behaviors shaped by digital technology, social media, and economic factors (Magano et al, 2020). Emotional intelligence (EI) is crucial for personal and professional success, influencing various aspects of life such as relationships, academic performance, and project management career advancement. Understanding and assess the emotional intelligence - basic soft skillset of Generation Z is essential for designing effective interventions and educational strategies tailored to their needs.
The research relies on the paradox, i.e. companies focus on integrating the newest generation into their operations without considering their full-scale advantages and disadvantages. This phenomenon will shift the companies into a suboptimal state which could be improved by means of analyzing the characteristics of Generation Z. Thus, the research analyzes Generation Z's soft skills, focusing on their relevance in project management. It aims to evaluate both general soft skills and those specific to project management among Generation Z university students. By identifying strengths and areas for improvement, tailored development plans will be proposed, utilizing tools like SWOT analysis. Additionally, the study acknowledges the importance of mitigating intergenerational tensions within project teams and proposes strategies like reversed mentoring. Overall, the research aims to provide actionable insights for leveraging Generation Z's soft skills effectively in project management contexts.

The research investigates two primary questions regarding Generation Z: Firstly, it identifies the strengths and weaknesses of Generation Z in terms of their soft skills and emotional intelligence competencies. Secondly, it examines whether Generation Z students who express an interest in becoming project managers, or are open to the idea, exhibit superior performance in these competencies compared to their peers.

This quantitative study will utilize surveys to evaluate the emotional intelligence of Generation Z university students who aspire to become project managers. The survey instrument, based on the Goleman-Boyatzis model (1995), will emphasize self-awareness, self-management, social awareness, and relationship management. Data will be collected online to ensure anonymity. The target sample size is approximately 300 students, recruited through convenience sampling across various universities and academic disciplines. Participants will rate themselves on a 1-5 Likert scale and complete informed consent and demographic questionnaires before the emotional intelligence survey. Statistical techniques, including descriptive statistics, correlation analysis, regression analysis, and Cronbach-alpha calculation, will be used to analyze the data. Notably, correlation analysis will be central to assessing the relationship between emotional intelligence scores and variables such as project management aspirations. This analysis aims to provide insights into the influence of emotional intelligence on career preferences among Generation Z university students.

The study and preparation of Generation Z graduates for the workforce offer significant benefits to both academia and the professional realm. Understanding their unique traits allows for tailored guidance during their transition into the job market. Innovative educational methods, particularly in project management, can equip them with essential skills while meeting their learning preferences. Anticipating and accommodating Generation Z's integration into organizations and projects ensures their seamless inclusion and maximizes their contributions. Additionally, targeted training programs address their specific developmental needs, fostering a skilled and motivated workforce capable of driving innovation and success.
References:

1. Nieto-Rodriguez (2021). Project Economy Has Arrived. Elérhető: https://hbr.org/2021/11/the-project-economy-has-arrived Letöltve: 2023.03.12.

2. Agrawal, N. M., & Thite, M. (2003). Nature and importance of soft skills in software project leaders. IIM Bangalore Research Paper, 214. Elérhető: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2159692 Letöltve: 2023.01.12.

3. Blaskovics, B. (2014). Az ICT szektorban működő projektvezetők személyes jellemzőinek hatása a projektsiker alakulására. Doktori disszertáció. Budapest: Budapesti Corvinus Egyetem.

4. Müller, R. & Turner, J. R. (2007). Matching the project manager's leadership style to project type. International Journal of Project Management, 25(1),p21-32.

5. Magano, J., & Silva, C. & Figueiredo, C. & Vitória, A. & Nogueira, T., & Dinis, M.A.P.. (2020). Generation Z: Fitting Project Management Soft Skills Competencies—A Mixed-Method Approach. Education Sciences. 10(7).

6. Voelkening, S. (2014). What is the soft-skill-set required by project managers and do Generation Y students in Ireland possess them?. Doctoral dissertation. Dublin: Dublin Business School).

7. Clarke, M. (2016). Addressing the soft skills crisis. Strategic HR review. 15(3) 137-139

8. Dean, S. A. (2017). Soft skills needed for the 21st century workforce. Doctoral dissertation. Minneapolis, MN: Walden University

9. Jones, M., Baldi, C., Phillips, C., & Waikar, A. (2017). The hard truth about soft skills: What recruiters look for in business graduates. College Student Journal, 50(3), 422-428.

10. Strauss, W. & Howe, N. (1992): Generations: The History of America's Future, 1584 to 2069. New York, NY: Harper Perennial.

11. Mannheim, K. (1952). "The Problem of Generations". In Kecskemeti, P. (ed.). Essays on the Sociology of Knowledge (pp. 276-320). New York, NY: Routledge.
# INFLUENCE OF BRAND COLLABORATION ON CONSUMER PERCEPTION

Aleksandra Zečević

PhD, Associate Professor

University of Belgrade, Faculty of Economics and Business – Department of Statistics and
Mathematics, Belgrade

e-mail: aleksandra.zecevic@ekof.bg.ac.rs

Katarina Nikolić

Junior data analyst (Fishingbooker, Booker group doo, Belgrade)

PhD student (University of Belgrade, Faculty of Economics and Business)

e-mail: katarinanan@gmail.com

Danilo Đurđić

Teaching Associate and PhD student

University of Belgrade, Faculty of Economics and Business – Department of Statistics and
Mathematics, Belgrade

e-mail: danilo.djurdjic@ekof.bg.ac.rs

## Abstract

In the contemporary marketing environment, where consumer attention is a valuable resource, brands are actively looking for innovative ways to attract audiences. Brand collaboration [10], such as the one that will be the topic of this paper, for example, between well-known brands like Opel and Plazma, is becoming a ubiquitous means of achieving this goal. However, while such marketing campaigns can bring obvious benefits in terms of wider audience reach [5], the question is how these campaigns affect the specific consumers' perceptions of brands that they are partnering with. Some research has already shown that brand collaboration is a strategy from which both partners benefit, regardless of whether those brands are perceived by consumers as high or low value. Although lower-value brands may benefit the most from this strategy, high-value brands are not put at a disadvantage, even when paired with a lower-value partner [13]. The value of the research will also be represented by the fact that two brands from different industries are being investigated, as well as the different types of products (ordinary and luxury).

The collaboration between brands such as Opel and Plazma seems to have the potential to bring together two different consumer sectors - car admirers and traditional biscuit lovers. This paper presents an introduction and guiding idea on how a specific marketing initiative affects the perception of the Opel brand, with an emphasized context of family values and traditions highlighted in the advertisement, which the Plazma brand possesses. Also, it will be considered how this initiative can shape the perception of the Plazma brand, which is now associated with the automotive industry. In this context, advertising has the potential to alter the perception of Opel brand making it recognizable as a family brand adapted to all generations. It can influence a change in consumer perception in a new positive direction, where Opel is seen as a brand that brings people together. In the study [8], it was found that developing brand affection can lead to an increase in trust, maintaining a connection with it, and believing in its future. In our case study, these conclusions would lead to significant value for the Opel brand.
Furthermore, the paper will examine the impact of brand partnerships on brand value perception and ways in which this perception can be conveyed to the target audience. Through an in-depth analysis of the research results, researchers will identify key factors contributing to the success or failure of such marketing campaigns. This will provide concrete guidelines for future marketing strategies involving brand partnerships, which can be beneficial to company management. Managers should be constantly aware of the potential for building and continually re-establishing the brand identity, and therefore the messages they convey to consumers should lead to current and future buyers feeling a connection with the brand [8].

The research methodology will include the use of questionnaires combined with A/B testing, which involves presenting advertising material resulting from the cooperation of Opel and Plazma brands to a selected group of participants. In parallel, the control group of participants will not be exposed to advertising material but will only answer questions from the questionnaire. This method will enable a comprehensive analysis of the impact of advertising on brand perception among participants who have been exposed to it. The aim of the research is to connect the results with general trends in co-branding and to provide practical advice to managers based on the data obtained on how effective these marketing strategies are in a changing market environment.

The use of the latest artificial intelligence tools, which can generate video recordings through sufficiently specific queries, may be of particular importance to company organization and management. This way, certain advertising and campaign materials can be tested without the high costs they usually entail. This research will precisely use this method; the Sora AI [15] platform will be used to generate a specific video that will be shown to participants. The study [9] pointed out that the application of artificial intelligence in companies will contribute to improving their marketing campaigns.

This research can be of exceptional importance for the organization and management of a company for several reasons. It enables a better understanding of the effectiveness of marketing strategies through the analysis of consumers' perceptions of marketing initiatives, especially through brand partnerships. In this way, it helps companies adjust their marketing efforts to achieve better results. It also identifies key success factors that shape positive consumers' attitudes towards brands, enabling management to focus resources on the most important aspects of the campaign. It can provide insight into the effectiveness of brand partnerships and how brand value perception is conveyed to consumers, which is useful for choosing future partners and optimizing existing collaborations. It enables companies to create competitive advantages through a better understanding of consumers and adapting marketing strategies accordingly, which can lead to differentiation and greater competitiveness in the market. Inc.com [14] emphasizes that co-branded partnerships are innovative because they are new, unexpected and increase brand awareness. These collaborations can strengthen the perception of product quality and lifestyle that brands represent, making brands more attractive, modern and interesting. Such collaborations can also increase consumer trust and attention, which are crucial for a successful organization and brand management.
References

1. Aaker, D. A., Kumar, V., & Day, G. S. (2004). *Marketing Research*. John Wiley & Sons.

2. Bruner, G. C., & Hensel, P. J. (2009). Marketing scales handbook. 5, A compilation of multi-item measures for consumer behavior & advertising research. American Marketing Assoc.

3. Cao, Z., & Yan, R. (2017). Does brand partnership create a happy marriage? The role of brand value on brand alliance outcomes of partners. Industrial Marketing Management, 67, 148-157.

4. Dev, C. S., Grzeskowiak, S., & Brown, J. R. (2011). Opportunism in brand partnerships: Effects of coercion and relationship norms. Cornell Hospitality Quarterly, 52(4), 377-387.

5. Farrelly, F., Quester, P., & Greyser, S. A. (2005). Defending the co-branding benefits of sponsorship B2B partnerships: The case of ambush marketing. Journal of Advertising Research, 45(3), 339-348.

6. Hague, P. N., Hague, N., & Morgan, C. A. (2004). Market research in practice: a guide to the basics. Kogan Page Publishers.

7. Helmig, B., Huber, J. A., & Leeflang, P. S. (2008). Co-branding: The state of the art. Schmalenbach Business Review, 60, 359-377.

8. Loureiro, S., Ruediger, K. & Demetris, V. Brand emotional connection and loyalty. J Brand Manag 20, 13-27 (2012). https://doi.org/10.1057/bm.2012.3

9. Nesterenko, Volodymyr/Olefirenko, Oleg (2023). The impact of AI development on the development of marketing communications. In: Marketing i menedžment innovacij 14 (1), S. 169 - 181.

10. Nunes, P. F., Dull, S. F., & Lynch, P. (2003). When two brands are better than one. Outlook, 1(1), 16-23.

11. Pinello, C., Picone, P. M., & Mocciaro Li Destri, A. (2022). Co-branding research: where we are and where we could go from here. European Journal of Marketing, 56(2), 584-621.

12. Sarstedt, M., & Mooi, E. (2014). A concise guide to market research. The Process, Data, and, 12.

13. Washburn, J. H., Till, B. D., & Priluck, R. (2000). Co-branding: Brand equity and trial effects. Journal of consumer marketing, 17(7), 591-604.

14. https://www/inc.com/michelle-greenwald/innovative-co-branding-and-creative-partnerships.html

15. https://openai.com/sora
# THE SIGNIFICANCE OF ARTIFICIAL INTELLIGENCE IMPLEMENTATION IN BUSINESS PROCESSES: IMPACT ON COMPANY PERFORMANCE AND EMPLOYEE PERCEPTION

**Katarina Božić**

University of East Sarajevo, Faculty of Business Economics Bijeljina

katarina.bozic@fpe.ues.rs.ba

**Theoretical background.** Artificial Intelligence (AI) significantly influences business by providing companies with the ability to optimize processes, enhance efficiency, and innovate at various levels, with the application of AI tools extending across a wide range of organizational business processes. Integrating AI into these processes potentially transforms the way companies operate, enhances their competitive advantage, and contributes to long-term success. Many authors have focused their research on the application of AI in business. However, relatively few organizations have applied artificial intelligence in the manufacturing aspect (Benbya, Davenport & Pachidi, 2020). Larson and DeChurch (2020) proposed two ways in which AI can be seen as a leader in the future. First, the focus on relationships should be expanded to include AI, and second, ways in which new AI tools can improve leaders' relational competencies should be explored (Larson & DeChurch, 2020). Authors Mikalef and Gupta in their research focus on identifying the resources needed for developing AI capabilities in enterprises, developing tools for measuring these capabilities, and examining the relationship between artificial intelligence and organizational performance. Empirical results confirm the theoretical framework and show that AI leads to improved creativity and organizational performance (Mikalef & Gupta, 2021). Managers need to understand artificial intelligence as supporting new business models, and researchers need to provide an analytical model for studying the impact of AI on organizations. This study emphasizes the significance of AI across various industries, and its results provide guidance for better leveraging the advantages of AI (Wamba-Taguimdje, Wamba, Kala Kamdjoug, & Tchatchouang Wanko, 2020). Authors Santos and Brito proposed and tested a performance measurement model for companies based on subjective indicators. The final model had six first-order dimensions: profitability, growth, customer satisfaction, employee satisfaction, social impact, and environmental impact (Santos & Brito, 2012). The phenomenon of artificial intelligence is being researched in many fields, and attention is also given to research on artificial intelligence in HRM (Tuffaha & Perello-Marin, 2022). In the study by Kambur and Akar (2021), a valid and reliable scale for studying employees' perception of artificial intelligence exclusively in human resource management was developed, showing that introducing AI into the training and development process can reduce the efforts required for training compared to traditional methods (Kambur & Akar, 2021). Management researchers should actively participate in researching the application of artificial intelligence in organizations and change their research approach to develop meaningful theory and practical advice (Raisch & Krakowski, 2021). In the last decade, technological advancements, including data analytics and AI, have significantly influenced the evolution of organizational processes and performance.

**Purpose of the study.** One of the main reasons for conducting this research is to gain a better understanding of how employees react to the implementation of artificial intelligence in business processes and how artificial intelligence affects the business performance of organizations. Learning about how employees perceive the implementation of AI can enable the identification of potential issues or advantages. This information is crucial for directing improvement strategies and better aligning with the needs of employees.
The research questions are:

RQ1: How does artificial intelligence affect company performance? (To what extent has the implementation of artificial intelligence positively affected the efficiency of processes within the company? How much has the introduction of artificial intelligence contributed to cost optimization? Has the use of artificial intelligence contributed to increased productivity within the company?).

RQ2: How do employees react to the integration of artificial intelligence into business operations? (How do employees perceive the introduction of artificial intelligence into work procedures? Do employees consider artificial intelligence an advantage or a challenge? How does the integration of artificial intelligence affect their satisfaction and motivation at work?).

**Design/Methodology.** The main dataset of this study will include all medium and large enterprises in the territory of Republic of Srpska in the business fields of information and communication technologies, energy, finance, trade, and transportation, listed on the official list of companies of the Chamber of Commerce of Republic of Srpska. The primary method of data collection in this research will be a survey. For the purpose of the study, two separate surveys will be conducted. The first will be designed to cover questions related to the efficiency of business processes, cost optimization, and productivity before and after the implementation of AI in business operations. The second survey will include a wide range of questions measuring employees' perception of the impact of artificial intelligence on business operations. The reason for conducting two surveys is the diversity of target groups; the first survey will be filled out by managers or owners of companies from different sectors, while the second survey will be filled out by employees in those organizations. To ensure reliability and honesty of respondents, these two surveys will be distributed separately and will be completely anonymous. Responses from both surveys, filled out by managers and employees, will be directly forwarded to the researcher. The condition for second survey is that it is exclusively filled out by employees involved in business processes who directly participate in business process operations. The validity of questionnaire items will be determined using Cronbach's alpha test. The data collection technique will be guided by a Likert judgment scale of five degrees. To this end, results will be created by taking the arithmetic mean for each dimension in the survey. After collecting the data, a series of statistical tests will be conducted, such as correlation tests, t-tests, and ANOVA to compare the mean values of operation efficiency, cost optimization, and productivity between different areas of enterprises implementing AI. Differences in business operations before and after the introduction of artificial intelligence into operations can be explored by using the Mann-Whitney U test. The variables selected for examining the impact of AI on process performance are: efficiency of business processes (operations), cost optimization, and productivity. For the purpose of the study, scaled ratings from 1 to 5 will be used for the efficiency of operations, cost optimization, and productivity at the enterprise level, while the variable "Introduction of artificial intelligence" will be defined as binary, with 0 representing ratings before introduction and 1 after the introduction of artificial intelligence into operations. A p-value of 0.05 will be used for making statistical conclusions in the study.

Construct validity is a type of validity that refers to the structural integrity of items in a measuring tool. The process of assessing the construct validity of a scale is typically done through factor analysis. Factor analysis could identify key factors related to employees' perceptions of the application of artificial intelligence and group similar responses into categories. This could assist management in better understanding employees' perceptions and making decisions regarding the implementation of A in business. This includes examining the correlation matrix, Kaiser-Meyer-Olkin test, and Bartlett's test.
Based on the results of factor analysis, dimensions reflecting the perception of change that artificial intelligence can bring to various aspects of business will be identified. Since categorical data are involved, appropriate values will be assigned to form a dataset with a certain number of variables. Such data can be further analyzed for descriptive statistics, determining the distribution of data and their graphical representation, as well as various assessments of the mean and variance at the sample level.

**Theoretical contribution.** The theoretical contribution of this research lies in a detailed analysis of literature about the impact of AI on business and employees' perceptions of AI integration into business processes. Additionally, it is important to identify key factors and mechanisms behind the successful implementation of AI in the business environments of medium and large enterprises. The focus is on understanding how AI affects the efficiency of business processes, cost optimization, and productivity, while also providing deeper insights into employees' perceptions of these changes.

**Practical implications.** The practical contribution of this work lies in providing a concrete methodology for investigating the effects of implementing artificial intelligence on business process performance, as well as measuring employees' perceptions of this impact. The research results can offer organizations guidance for implementing AI technologies into their operations, which can result in process optimization, cost reduction, and increased productivity.

**Keywords:** artificial intelligence, business processes, enterprises, performance, employees

## REFERENCES

1. Benbya, H., Davenport, T. H., & Pachidi, S. (2020). Artificial intelligence in organizations: Current state and future opportunities. MIS Quarterly Executive, 19(4).

2. Kambur, E., & Akar, C. (2021). Human resource developments with the touch of artificial intelligence: a scale development study. *International Journal of Manpower*, 168-205. DOI: 10.1108/IJM-04-2021-0216

3. Larson, L., & DeChurch, L. A. (2020). “Leading teams in the digital age: four perspectives on technology and what they mean for leading teams. *The Leadership Quarterly*, 31, 1-18. DOI:10.1016/j.leaqua.2019.101377

4. Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. *Information & Management*, DOI:10.1016/j.im.2021.103434.

5. Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation-augmentation paradox. *Academy of management review*, 46(1), 192-210. DOI:10.5465/2018.0072

6. Santos, J., & Brito, L. A. (2012). Toward a Subjective Measurement Model for Firm Performance. *BAR - Brazilian Administration Review*, 96-117. DOI:10.1590/S1807-76922012000500007

7. Tuffaha, M., & Perello-Marin, M. R. (2022). Adoption Factors of Artificial intelligence in Human Resources Management. *Future of Business Administration*, 1(1), 1-12. DOI: 10.33422/fba.v1i1.140

8. Wamba-Taguimdje, S., Wamba, S. F., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E. (2020). Influence of Artificial Intelligence (AI) on Firm Performance: The Business Value of AI-based Transformation Projects. *Business Process Management Journal*.
Lovrenc Švegl, prof. dr. Miha Škerlavaj

School of Economics and Business, University of Ljubljana, PhD student - Management and
Organization, Mentor: prof. dr. Miha Škelavaj, Ljubljana, Slovenia

Presenting Author: Lovrenc Švegl

Theoretical Background

The advent of Artificial Intelligence (AI) in the workplace has ushered in a new era of potential for employee creativity and innovation. The theoretical framework of this study intertwines several key theories to paint a comprehensive picture of how AI can be effectively integrated into employees' work spheres.

Transformational Leadership Theory is instrumental in establishing a vision for AI integration, where leaders inspire their workforce and create a culture that embraces change and innovation (Rafferty & Griffin, 2004) (Antonakis & House, 2014). This form of leadership doesn't stand alone; it deeply intertwines with Creative Self-Efficacy Theory, suggesting that an employee's belief in their creative capacities is magnified under a transformational leader, fostering a readiness to engage with AI (Mittal & Dhar, 2015). In the complex interaction between people and computers at work, Self-Determination Theory (SDT) adds another layer, positing that the intrinsic motivation of employees, nurtured by a transformational leadership style, leads to a higher quality of AI interaction and utilization (Bass & Steidlmeier, 1999) (Ryan & Deci, 2000). This is where the Leader-Member Exchange (LMX) Theory comes into play, delineating the caliber of interaction between a leader and their team members as a mediator in this relationship, influencing the degree to which employees trust and decide to use AI systems (Graen & Uhl-Bien, 1995).

Thus, the theoretical background of this research presents a dynamic interplay where transformational leadership not only empowers employees through enhanced self-efficacy but also satisfies intrinsic motivational needs, which, when coupled with strong leader-member relationships, is hypothesized to lead to increased intention to use AI and ultimately, higher levels of employee creativity.

<figure><img src="image_23.png" /><figcaption>Figure 1: Conceptual Research Model</figcaption></figure>
## Purpose of Study

The purpose of this study is to investigate how employees' knowledge of AI and their trust in AI output influence their intention to use AI, and how this intention, shaped by transformational leadership, impacts their creativity at work. The study aims to dissect the complex interactions between these variables and understand their collective effect on fostering an innovative and technologically adaptive workforce. Through this research, I seek to contribute to the broader understanding of AI's role in enhancing employee creativity, crucial for organizational growth and adaptability in an increasingly digital world.

## Method

Initially, data will be collected through structured survey questionnaires administered to employees. Once the data collection phase will be complete, the study will employ Structural Equation Modeling (SEM) to analyze the data.

## Findings

Drawing from the interwoven theories and existing literature, my research anticipates findings that will shed light on the catalyst role of transformational leadership in enhancing the AI adoption curve among employees. I expect to reveal a positive influence of employee knowledge of AI and their trust in AI output on their intention to utilize AI in their tasks. This increased intention to use AI is hypothesized to lead to a surge in perceived employee creativity, offering new insights into the facilitation of an AI-empowered workforce.

## Theoretical Contribution

The theoretical contribution of this research is multifaceted. By exploring the intersection of transformational leadership and AI use in the workplace, it aims to enhance the Transformational Leadership Theory by providing empirical evidence on how such leadership affects employees' acceptance and use of AI technology. Moreover, it seeks to expand Creative Self-Efficacy Theory by examining the role of AI in shaping employees' beliefs in their creative capabilities. The Self-Determination Theory (SDT) will be deepened by investigating how different factors influence using AI, potentially contributing to the SDT literature by integrating AI technology specific factors. Finally, this research will contribute to Leader-Member Exchange (LMX) Theory by demonstrating how the quality of leader-member relationships can impact creative behavior derived from the AI use intention. In essence, this study will offer new insights into how these established theories operate within the novel context of AI in the workplace.

## Practical Implications

The practical implications of this research will be significant for organizations looking to harness the potential of AI in the workplace. The findings will provide actionable insights on how leadership styles, particularly transformational leadership, can influence employees' trust in AI and their intention to use such technologies. Additionally, the results will offer guidance on how to improve AI-related training and knowledge dissemination to enhance employee confidence in using AI, which could lead to greater creativity and innovation. By understanding these dynamics, organizations can develop targeted interventions to foster a more receptive AI culture, optimize AI deployment strategies, and ultimately improve overall performance and competitive advantage.

## Keywords

Transformational Leadership, Artificial Intelligence Adoption, Creative Self-Efficacy, Employee Creativity, Leader-Member Exchange, Trust in AI Output
References

1. Antonakis, J., & House, R. J. (2014). Instrumental leadership: Measurement and extension of transformational-transactional leadership theory. *The Leadership Quarterly*, 25(2014), 746-771. https://doi.org/10.1016/j.leaqua.2014.04.005.

2. Bass, B. M., & Steidlmeier, P. (1999). Ethics, character, and authentic transformational leadership behavior. *Leadership Quarterly*, 10(2), 181–217.

3. Graen, G. B., & Uhl-Bien, M. (1995). Relationship-based approach to leadership: Development of leader-member exchange (LMX) theory of leadership over 25 years: Applying a multi-level multi-domain perspective. *Leadership Quarterly*, 6(2), 219-247.

4. Mittal, S., & Dhar, R. L. (2015). Transformational leadership and employee creativity: Mediating role of creative self-efficacy and moderating role of knowledge sharing. *Management Decision*, 53(5), 894-910. https://doi.org/10.1108/MD-07-2014-0464.

5. Rafferty, A. E., & Griffin, M. A. (2004). Dimensions of transformational leadership: Conceptual and empirical extensions. *The Leadership Quarterly*, 15(2004), 329-354. https://doi.org/10.1016/j.leaqua.2004.02.009

6. Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. *American Psychologist*, 55(1), 68-78. doi:10.1037/0003-066X.55.1.68.
# THE ENABLERS OF SUCCESSFUL ARTIFICIAL INTELLIGENCE ADOPTION IN COMPANIES

Dejan Uršič

University of Ljubljana, School of Economics and Business Kardeljeva ploščad 17, SI-1000 Ljubljana, Slovenia

E-mail: dejan.ursic@ef.uni-lj.si

**Keywords:** artificial intelligence, enablers, resources, knowledge-based view, company

## BACKGROUND

With the exponential development and growth in the field of artificial intelligence (AI) tools and technologies, companies are adopting these disruptive technologies at an increasingly rapid rate, expecting to achieve higher productivity, cost savings, process transparency, more profitable business models, and better workplace conditions (Čater et al., 2021; Mikalef & Pateli, 2017). The adoption and utilization of new technologies are key constructs of interest in the information management field, with scholars typically building upon robust theoretical frameworks such as TOE (Depietro et al., 1990), TAM (Davis, 1989) and UTAUT (Venkatesh et al., 2003) to discuss successful technology adoption in companies. A similar conclusion can be drawn for AI, with most studies leveraging the TOE framework (Alsheibani et al., 2019; Bhattacharyya & Shah, 2021; Kar & Kushwaha, 2021; Kinkel et al., 2022; Nguyen et al., 2022; Seethamraju & Hecimovic, 2022). However, there is still a need in the existing literature to identify the internal company factors that enable the adoption of AI technologies, which is crucial for leveraging their full potential.

## PURPOSE OF THE STUDY

By building on the resource-based view theory (Barney, 1991), I aim to identify the resources that companies must possess to successfully adopt and subsequently use AI technologies. Resources serve as enablers, facilitating the deployment of AI technologies in companies. Drawing on existing literature on enablers/barriers to new technology use (Čater et al., 2021; Oliveira Neto et al., 2017), four types of resources have been identified: cultural, human, financial, and organisational. To expand my research model further, I will include the constructs of digital process innovation and digital product innovation as consequences of AI technology adoption, reflecting how companies can leverage AI in the innovation process (Bahoo et al., 2023). I will examine the mediating effect of AI between company resources and digital innovation to understand the nuanced relationships within this framework. Additionally, I will conduct a dominance analysis (Budescu & Azen, 2004; Tonidandel & LeBreton, 2011) to determine which type of resources contributes most to the adoption of AI technology, providing insights into the relative importance of each type of resource.

## METHOD

As this is a work-in-progress, data collection is ongoing. I am using a questionnaire to collect the primary data from executives of large and medium-sized companies across various industries in Slovenia. The operationalization of the variables in my research model is based on earlier research, with some minor modifications to better fit the context of my study. Respondents are expressing their agreement with specific statements using a 7-point Likert scale. Company size and industry type are included as control variables to account for their potential influence on the outcomes. To test the relationships between the constructs in my research model, I will conduct a covariance- based structural equation modelling (SEM) analysis.
## FINDINGS (EXPECTED)

I anticipate that the results will confirm the positive relationship of the four types of resources with the adoption of AI technology. Similarly, the results should demonstrate a positive relationship between AI adoption and both digital process and product innovation. Lastly, I expect the analysis to reveal either a partial or full mediating effect of AI adoption on the relationships between company resources and digital process and product innovation.

## THEORETICAL CONTRIBUTION

This paper aims to address the following research gaps. First, by building on the resource-based view, I aim to enhance the current understanding of AI by analysing which internal organizational factors contribute to its adoption. Given the predominance of qualitative studies in this area, a quantitative approach is employed to examine the relationships between these constructs, offering a different perspective on the dynamics of AI adoption. Second, through a dominance analysis, a statistical method to identify the most influential predictors, I aim to clarify which resources are most critical for the successful adoption of AI technology. Finally, I intend to corroborate existing literature on AI by demonstrating that it serves as a significant precursor to digital innovation and plays a pivotal role in amplifying the impact of company resources on digital innovation.

## PRACTICAL IMPLICATIONS

My research aims to develop a meaningful framework that outlines the practical implications of leveraging company resources for AI technology adoption and enhancing digital innovation. This study will clarify which resources are critical for AI integration, providing executives with strategic guidelines for prioritizing resource allocation and acquisition. Additionally, the research will offer insights into optimizing the use of AI to streamline various aspects of the innovation process, from ideation to product development, thereby facilitating the creation of competitive market offerings.

## REFERENCES

1. Alsheibani, S. A., Cheung, D., & Messom, D. (2019). Factors inhibiting the adoption of artificial intelligence at organizational-level: A preliminary investigation. AMCIS.

2. Yahoo, S., Cucculelli, M., & Qamar, D. (2023). Artificial intelligence and corporate innovation: A review and research agenda. *Technological Forecasting and Social Change, 188*, 122264. https://doi.org/10.1016/j.techfore.2022.122264

3. Barney, J. (1991). Firm resources and sustained competitive advantage. *Journal of Management, 17*(1), 99-120.

4. Bhattacharyya, S. S., & Shah, Y. (2021). Emerging technologies in Indian mining industry: an exploratory empirical investigation regarding the adoption challenges. *Journal of Science and Technology Policy Management*.

5. Budescu, D. V., & Azen, R. (2004). Beyond Global Measures of Relative Importance: Some Insights from Dominance Analysis. *Organizational Research Methods, 7*(3), 341-350. https://doi.org/10.1177/1094428104267049

6. Čater, T., Čater, B., Černe, M., Koman, M., & Redek, T. (2021). Industry 4.0 technologies usage: motives and enablers. *Journal of Manufacturing Technology Management, 32*(9), 323-345. https://doi.org/10.1108/JMTM-01-2021-0026

7. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. *MIS Quarterly, 13*(3), 319-340. https://doi.org/10.2307/249008
8. Depietro, R., Wiarda, E., & Fleischer, M. (1990). The context for change: Organization, technology and environment. *The Processes of Technological Innovation, 199*(0), 151–175.

9. Kar, A. K., & Kushwaha, A. K. (2021). Facilitators and barriers of artificial intelligence adoption in business–insights from opinions using big data analytics. *Information Systems Frontiers*, 1–24.

10. Kinkel, S., Baumgartner, M., & Cherubini, E. (2022). Prerequisites for the adoption of AI technologies in manufacturing – Evidence from a worldwide sample of manufacturing companies. *Technovation, 110*, 102375.

11. https://doi.org/10.1016/j.technovation.2021.102375

12. Mikalef, P., & Pateli, A. (2017). Information technology-enabled dynamic capabilities and their indirect effect on competitive performance: Findings from PLS-SEM and fsQCA. *Journal of Business Research*, 70, 1–16.
https://doi.org/10.1016/j.jbusres.2016.09.004

13. NGUYEN, T. L., NGUYEN, V. P., & DANG, T. V. D. (2022). Critical Factors Affecting the Adoption of Artificial Intelligence: An Empirical Study in Vietnam. *The Journal of Asian Finance, Economics and Business*, 9(5), 225–237.

14. Oliveira Neto, G. C., Leite, R. R., Shibao, F. Y., & Lucato, W. C. (2017). Framework to overcome barriers in the implementation of cleaner production in small and medium-sized enterprises: Multiple case studies in Brazil. *Journal of Cleaner Production*, 142, 50–62.
https://doi.org/10.1016/j.jclepro.2016.08.150

15. Seethamraju, R., & Hecimovic, A. (2022). Adoption of artificial intelligence in auditing: An exploratory study. *Australian Journal of Management*, 03128962221108440.
https://doi.org/10.1177/03128962221108440

16. Tonidandel, S., & LeBreton, J. M. (2011). Relative Importance Analysis: A Useful Supplement to Regression Analysis. *Journal of Business and Psychology*, 26(1), 1–9.
https://doi.org/10.1007/s10869-010-9204-3

17. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. *MIS Quarterly*, 27(3), 425–478.
https://doi.org/10.2307/30036540
UNDERSTANDING THE RELATIONSHIP BETWEEN THE MEANING OF WORK AND
WORK-RELATED IDENTITY LOSS IN RETIREMENT DYNAMICS

Ana Bartol

University of Ljubljana, School of Economics and Business, Slovenia

Barbara Grah

University of Ljubljana, School of Economics and Business, Slovenia

Darja Peljhan

University of Ljubljana, School of Economics and Business, Slovenia

Theoretical background

Work is an important part of people's lives, providing routine and the many activities, functions, and rewards on which they depend to a greater or lesser extent (Eagers et al., 2018; Silver & Williams, 2018; Pratt et al., 2003). Work is closely linked to our identity, and WRI is a significant part of an individual's overall identity (Walsh & Gordon, 2008). Several studies have examined identity in relation to work, for example, identity changes following job loss (Hetschko et al., 2014; Papa & Lancaster, 2015), and WRI loss in the face of changes in the workplace (Conroy & O'Leary-Kelly, 2014). Fasbender et al. (2016) found a positive link between the meaning of work and post-retirement employment, specifically that the meaning of work is important for post-retirement decisions. Studies have shown that participants who placed work above all else fostered negative attitudes towards retirement (Silver & Williams, 2018) and that the transition into retirement is particularly difficult for individuals with a strong work identity (Kragt et al., 2017). Many individuals perceive their work aspirations from different perspectives: as a job where the main focus is on financial reward and the necessity of employment, rather than on enjoyment or satisfaction; as a career characterized by progression and advancement; or as a profession where the main focus is on the enjoyment that comes from doing fulfilling and socially rewarding work (Bellah, et al., 1985). In this research we use Mor- Barak's (1995) concept of the meaning of work for older adults, containing four factors: (1) social dimension, referring to the need to interact with people in the workplace; (2) personal dimension, referring to the need for getting personal satisfaction, self-esteem, and pride in the work and self; (3) financial dimension, referring to the material needs; and (4) generativity, referring to the need of transferring the knowledge and skill to younger generations.

We propose the following hypotheses:

H1a: Social meaning of work is positively related to WRI loss

H1b: Personal meaning of work is positively related to WRI loss

H1c: Financial meaning of work is positively related to WRI loss

H1d: Generative meaning of work is positively related to WRI loss

Purpose of the study

Although retirement is an eagerly awaited life change for many, the loss of important work- related activities and social ties can have an impact on stability and positive identity (Jolles et al., 2022; Kragt et al., 2017; Osborne, 2012; Wang, 2007; Wang & Shi, 2014). This paper aims to raise awareness of the connection between the meaning of work and WRI loss and to provide a deeper understanding of the challenges faced by older workers approaching and experiencing retirement in relation to their WRI loss. Furthermore, this research aims to test the measurement scales of the meaning of work and WRI loss and to examine the relationship between the meaning of work and WRI loss, and identify possible moderators.
Method

This abstract is a part of a larger study with a focus on the relationship between the meaning of work and the WRI loss. The methodology used in this document is based on qualitative research with older people approaching, entering, or living in retirement, as well as with experts in the field of aging and age management. To collect the data, an in-depth interview with open-ended questions is used. By interviewing people approaching, moving through, or living in retirement, we aim 1) to get a better understanding of the relationship between the meaning of work and WRI loss, and 2) to identify potential moderators between the constructs to conceptualize the final model (Amabile, 2019). We also administered the measurement instruments for the meaning of work and WRI loss to the experts in the field of aging and age management to validate the measures and reasonableness of constructs included in the conceptual model.

Findings

As this study is a work in progress, we assume that the findings will reveal the importance of understanding how different facets of the meaning of work affect WRI loss and its consequences. We expect that results will show that the transition and adjustment to retirement is particularly difficult for individuals with a strong WRI and a high meaning of work.

Contributions

This paper has several contributions. Theoretically, the research will be the first according to our knowledge to examine how the meaning of work is related to WRI loss before and after retirement. Further, we contribute to the existing literature by extending the knowledge about WRI loss in the context of retirement. The use of the qualitative method provides a deeper understanding of the challenges people are facing due to retirement, specifically the issue of WRI loss. Methodologically we also contribute with the evaluation of the measurements' content validity.

Practical implications

By deepening the knowledge of the relationship between the meaning of work and WRI loss related to the retirement process, which often leads to negative health outcomes for a retiree, this research has important practical implications. It offers practical pieces of advice at individual, organizational, and national levels on what actions to take to ease the transition of the individual to retirement, to experience WRI loss to a lesser degree, related to social, personal, financial and, generativity dimensions of the meaning of work. For example, we assume that an individual worker, who has accumulated enough financial assets throughout the working period, will experience WRI loss to a lesser degree related to the financial meaning of work. Therefore, managers could offer their employees different financial planning training and initiatives earlier in their careers. Also, individuals should start planning their financial investments and ensure their financial stability for their post-retirement period. Nevertheless, also at the national level, financial literacy should become an important dimension in educational curriculums at primary, secondary, and tertiary levels.

**Keywords:** retirement, age management, work-related identity, meaning of work
References

1. Amabile, T. M. (2019). Understanding Retirement Requires Getting Inside People's Stories: A Call for More Qualitative Research. *Work, Aging and Retirement, 5*(3), 207–211. https://doi.org/10.1093/workar/waz007

2. Bellah, R. N., Madsen, R., Sullivan, W. M., Swidler, A., & Tipton, S. M. (1985). *Habits of the Heart*. New York: Harper & Row.

3. Conroy, S. A., & O'Leary-Kelly, A. M. (2014). Letting Go and Moving On: Work-Related Identity Loss and Recovery. *Academy of Management Review, 39*(1), 67–87. https://doi.org/10.5465/amr.2011.0396

4. Eagers, J., Franklin, R. C., Broome, K., & Yau, M. K. (2018). The influence of work on the transition to retirement: A qualitative study. *British Journal of Occupational Therapy, 81*(11), 624–632. https://doi.org/10.1177/0308022618766244

5. Fasbender, U., Wang, M., Voltmer, J.-B., & Deller, J. (2016). The Meaning of Work for Post-retirement Employment Decisions. *Work, Aging and Retirement, 2*, 12–23. https://doi.org/10.1093/workar/wav015

6. Hetschko, C., Knabe, A., & Schöb, R. (2014). Changing Identity: Retiring from Unemployment. *The Economic Journal, 124*(575), 149–166. https://doi.org/10.1111/ecoj.12046

7. Jolles, D., Lamarche, V. M., Rolison, J. J., & Juanchich, M. (2022). Who will I be when I retire? The role of organizational commitment, group memberships and retirement

8. transition framing on older worker's anticipated identity change in retirement. *Current Psychology*. https://doi.org/10.1007/s12144-022-02869-7

9. Kragt, D., Jorritsma, K., Dunlop, P., & Parker, S. (2017). *Firefighters' Transition Into Retirement: Issues, Challenges And Support Program Design*. The University of Western Australia.

10. Mor-Barak, M. E. (1995). The Meaning of Work for Older Adults Seeking Employment: The Generativity Factor. *The International Journal of Aging and Human Development, 41*(4), 325–344. https://doi.org/10.2190/VGTG-EPK6-Q4BH-Q67Q

11. Osborne, J. W. (2012). Psychological Effects of the Transition to Retirement Effets psychologiques de la transition vers la retraite.

12. Papa, A., & Lancaster, N. (2015). Identity continuity and loss after death, divorce, and job loss. *Self and Identity, 15*. https://doi.org/10.1080/15298868.2015.1079551

13. Pratt, M., Ashforth, B., Cameron, K., Dutton, J., & Quinn, R. (2003). Fostering meaningfulness in working and at work. *Positive Organizational Scholarship: Foundations of A New Discipline*, 309–327.

14. Silver, M. P., & Williams, S. A. (2018). Reluctance to Retire: A Qualitative Study on Work Identity, Intergenerational Conflict, and Retirement in Academic Medicine. *The Gerontologist*, 58(2), 320–330. https://doi.org/10.1093/geront/gnw142

15. Wang, M. (2007). Profiling retirees in the retirement transition and adjustment process: Examining the longitudinal change patterns of retirees' psychological well-being. *Journal of Applied Psychology, 92*(2), 455–474. https://doi.org/10.1037/0021-9010.92.2.455

16. Wang, M., & Shi, J. (2014). Psychological Research on Retirement. *Annual Review of Psychology, 65*(1), 209–233. https://doi.org/10.1146/annurev-psych-010213-115131
Škerlavaj Miha

School of Economics and Business, University of Ljubljana, Academic Unit for Management
and Organization Ljubljana, Slovenia

E-mail: [miha.skerlavaj@ef.uni-lj.si](mailto:miha.skerlavaj@ef.uni-lj.si)

Kaloh Sarina

School of Economics and Business, University of Ljubljana, Academic Unit for Management
and Organization Ljubljana, Slovenia

E-mail: [sarina.kaloh@gmail.com](mailto:sarina.kaloh@gmail.com)

**Keywords:** Supervisor Sleep, Work Intensity, Post-Heroic Leadership (PHL), Motivation To lead (MTL), Leader-Member Exchange (LMX)

ABSTRACT

In a rapidly changing work environment characterized by demands for constant connectivity and work intensification, the well-being and performance of leaders play a crucial role in organizational success. Shareholders' increasing demands for organizational success often come at the expense of individuals working longer hours and sacrificing their sleep time. This trend is particularly detrimental to leaders who must also navigate interpersonal dynamics between followers to achieve results. This study aims to explain the relationship between leader's work intensity, their sleep and the way of leading.

Drawing on the Job Demands-Resources (JD-R) theory, our longitudinal study of 30 leaders and followers in diverse organizational settings employs a comprehensive methodology integrating different measures of sleep quality, leadership behaviors, and outcomes (e.g. Servant and Shared Leadership, Leader's Motivation to Lead (MTL), Follower's Detachment from Work). Using experience-sampling methods (ESM) combined with wearable technology for sleep monitoring, we will collect observations over a designated period.

This study contributes to both theoretical and practical domains. It contributes to the literature by examining the impact of leaders' work intensity as an independent variable on the quality of their sleep. By investigating the relationship between workload and sleep quality, we aim to elucidate how variations in workload affect the sleep patterns of leaders, subsequently influencing the expression of post-heroic leadership traits. Specifically, we explore how sleep quality moderates the relationship between workload and the manifestation of post-heroic leadership behaviors.

Our first contribution is theoretical, since through this comprehensive study, we seek to provide a nuanced understanding of how leaders' workload and sleep quality interact to shape leadership behavior and its outcomes in organizational settings. Based on the theories of JD-R model, Post-heroic leadership, Restricted Employee Sustainability Theory (REST) we aim to understand how workload affects sleep and how leaders' sleep quality influences post-heroic leadership, Motivation to Lead (MTL), and Follower's Detachment from Work.
Our second contribution lies in its empirical nature. By employing a multimethod approach, based on the conducted longitudinal study in a natural environment, that integrates quantitative and qualitative data, our study contributes to methodological advancements in leadership research. Such an approach represents a unique combination of the daily ESM and a variety of sleep measures—a methodological approach that is valuable both for obtaining a better understanding of causality in the proposed model and for digging deeper into the interplay between sleep and work phenomena.

Since researchers primarily focus was individual-level, person-centered variables, and their interactions, such as traits and personality, we go deeper to explore the empirical findings studying Leader-Member Exchange (LMX) as an outcome, which is our third contribution. Our study distinguishes between outcomes tied to the leader's characteristics and those more relational to the followers, thereby offering a multifaceted understanding of leadership dynamics. This multimethod approach significantly enriches the existing theory of leadership.

Lastly, our findings offer valuable insights for organizational leaders and practitioners. By elucidating the interplay between post-heroic leadership, sleep quality, and outcomes related to leader engagement, this study provides actionable guidance for leaders striving to navigate the challenges of a rapidly changing work environment while maintaining their well-being and enhancing their leadership effectiveness.
Maša Košak; prof. dr. Robert Kaše, Full Professor, prof. dr. Matej Černe, Full Professor

**Affiliations:** School of Economics and Business, University of Ljubljana, PhD student - Management and Organization, under the mentorship of: prof. dr. Robert Kaše, Full Professor, prof. dr. Matej Černe, Full Professor

## Theoretical background

Individuals differ in their general propensity towards **proactivity**. Proactive personality is a stable individual trait (Bateman and Crant, 1993) that shows in many ways, such as identifying opportunities, showing initiative, or taking action. However this being a stable personality trait, any individual can show proactive behavior depending on their motivation and situation (Parker, no date). Proactive behavior in the workplace refers to the active decision-making of an individual in their work environment (Grant & Ashford, 2008), and patterns of proactive behaviors in the workplace are also shown in the process of employee socialization, through different behaviors, such as seeking feedback, or general networking (Grant in Ashford, 2008). Proactive behavior has a positive impact on **work relationships** through seeking opportunities for interaction and through active relationship building in the workplace (Parker, Williams & Turner, 2006). With the rise of **hybrid work**, the workplace relationships have changed (De Smet, Dowling, Mysore & Reich, 2021). In virtual and hybrid work, the quality of relationships is greatly affected by reduced interaction between employees (Wessinger, 2020), and when working from home, employees lose the opportunity to spontaneously walk to a colleague's desk and talk about work (and other) matters (Dahik et al., 2020).

## Purpose of study

The purpose of the study is to examine **the role of hybrid work for proactivity in work relationships**, in order to prevent the impoverishment of work relations in the increasingly common forms of hybrid work introduced by organizations. The study aims to better understand the role of hybrid work as a work context for the proactivity of individuals in work relationships and to discover the role of proactivity as a personality trait for proactivity in work relationships.

## Method

The study is based on a multivariate regression analysis of a questionnaire based on the measurement of proactive socialization tactics, the measurement of the individual's proactive personality and the measurement of the way of working in relation to the possibilities of hybrid work. The research answers the following research question: *What is the role of hybrid work for proactivity in work relationships?*

## Findings

Results of the analysis show that (1) individuals with a more proactive personality more often behave proactively in work relationships, (2) that individuals who work hybrid more often behave proactively in work relationships, and (3) that the number of days of remote work, when an individual works remotely up to and including 4 days per week, has a positive effect on the frequency of behaviors in the context of proactive socialization tactics. In contrast, the analysis of individuals who work only remotely, reveals that (4) individuals who only work remotely, are on average, less proactive in their work relationships.
Work away from the office has thus a negative impact on proactivity in work relationships, however hybrid work, when an individual works remotely up to and including 4 days a week, has a positive impact on proactive socialization at the workplace. **This study shows an inverted U-curve**, which means that both extremes - working only in the office and working only remotely - are worse than the optimal way of working, which is hybrid work.

## Theoretical contribution

There are many studies done separately in the field of proactivity, work relationships and hybrid work, however there is not much research done uniting the three fields and researching them simultaneously. Several studies accurately describe the intersections of two individual themes, but this work contributes to the theory of all the three topics: the role of hybrid work as a work context for proactivity in work relationships.

## Practical implications

The findings of the research contribute greatly to the HR and managerial practices in organizations when it comes to setting up the hybrid work policies. The inverted U-curve can help organizations understand that while allowing their employees to occasionally work from home, this can increase the proactivity in the work relationships, however when allowing employees to only work remote, the proactivity in relationships will decrease.

The research also contributes to the understanding of changing relationships due to hybrid work or remote work. Proactivity in work relationships is an important predictor of the quality of the relationship (Parker, Williams & Turner, 2006), but it is not the only one. According to the results of this research, we can claim that hybrid work has a positive effect on proactivity in work relationships, which is an important predictor of the quality of the work relationship, but full-time remote work has a negative effect on it.

**Keywords:** Proactivity at the workplace, proactive personality, proactive behaviour, hybrid work, remote work, work relationships.
REFERENCES:

1. Bateman, T. S. & Crant, J. M. (1993). The proactive component of organizational behaviour: a measure and correlates. *Journal of Organizational Behavior, 14*(2), 103-118.

2. Dahik, A., Lovich, D., Kreafle, C., Bailey, A., Kilmann, J., Kennedy, D., Roongta, P., Schuler, F., Tomlin, L. & Wenstrup, J. (2020). BCG. *What 12,000 Employees Have to Say About the Future of RemoteWork*. Retrieved March 2022 from https://www.bcg.com/publications/2020/valuable-productivity-gains-covid-19?utm_medium=Email&utm_source=esp&utm_campaign=none&utm%E2%80%A6%201/16

3. De Smet, A. Dowling, B., Mysore, M. & Reich, A. (2021). McKinsey & Company. It's time for leaders to get real about hybrid. Retrieved April 2022 from https://www.mckinsey.com/business-functions/people-and-organizational-performance/our-insights/its-time-for-leaders-to-get-real-about-hybrid

4. Grant, A. M. & Ashford, S. J. (2008). The dynamics of proactivity at work. *Research in organizational behaviour, 28*, 3-34.

5. Parker, S. K. (no date). What is proactivity? Google Sites. Retrieved February 2022 from https://sites.google.com/site/profsharonparker/proactivity-research/what-is-proactivity

6. Parker, S. K., Williams, H. M. & Turner, N. (2006). Modeling the Antecedents of Proactive Behavior at Work. *Journal of Applied Psychology, 91*(3), 636-52.

7. Wessinger, J. A. (2020). The importance of relationship-building in virtual environments. *CUInsight*. Retrieved February 2022 from https://www.cuinsight.com/the-importance-of-relationship-building-in-virtual-environments/
## UNLOCKING ATHLETIC POTENTIAL: THE MEDIATING INFLUENCE OF SLEEP ON STRESS AND ENGAGEMENT – EXTENDED ABSTRACT

Assist. **Jure Andolšek**, Master of Business Studies, School of Economics and Business, University of Ljubljana, Professor PhD. **Matej Černe**, School of Economics and Business, University of Ljubljana, Professor PhD. **Tomaž Čater**, School of Economics and Business, University of Ljubljana, Associate Professor PhD. **Primož Pori**, Faculty of sport, University of Ljubljana, Professor PhD. **Miha Škerlavaj**, School of Economics and Business, University of Ljubljana, assist. **Amadeja Lamovšek**, Master of Business Studies, School of Economics and Business, University of Ljubljana

### Theoretical background

In the world of professional sports, a common challenge that athletes face is balancing the stress from their intense and competitive environments with the need for quality sleep (Amaral et al. 2018). Stress, especially when linked to high-performance demands, not only disrupts an athlete's sleep by making it hard to fall asleep and stay asleep but also reduces the quality and quantity of sleep they get (Åkerstedt, 2006; Walsh et al., 2021). This is a big problem because sleep is crucial for recovery and performance (Watson, 2017). When athletes don't get enough good sleep, it's harder for them to stay mentally and physically sharp, which can make them less engaged and less effective in their sport (Barnes et al., 2013). To understand this issue better, we look at two important theories: the Job Demands-Resources (JDR) model and the Effort-Recovery Model. The JDR model helps us see how the tough parts of being an athlete can lead to problems if athletes don't have the right resources, like enough good sleep, to help them cope (Bakker & Demerouti, 2007). On the other hand, the Effort-Recovery Model tells us that getting good rest and recovery, mainly through sleep, is essential for athletes to bounce back from the demands of their sport, avoid burnout, and maintain high levels of engagement and performance (Barnes, 2013).

### Purpose of study

The purpose of this study is to explore the mediating role of sleep in the relationship between stress and engagement among professional handball players. By integrating the Job Demands-Resources (JDR) model and the Effort-Recovery Model, we aim to understand how stress impacts sleep quality and, in turn, how sleep quality affects athletes' engagement levels. This research seeks to provide empirical evidence on the significance of sleep as a critical recovery mechanism and personal resource that can mitigate the negative effects of stress, thereby enhancing athlete engagement and offering insights for targeted interventions to improve athlete well-being and performance.

### Method

This research involved data from two professional (male – 20 participants and female – 19 participants) handball clubs in Slovenia, collected over a period of 30 days. Data were collected longitudinally using an experience-sampling method. This approach is effective for capturing daily psychological and physiological states in real-world settings (Hektner, Schmidt, & Csikszentmihalyi, 2007). Participants were provided with Oura rings, which are validated tools for objective sleep monitoring, capturing metrics such as total sleep duration, sleep latency, and deep sleep (Arnal et al., 2020).
Complementing the objective data, daily surveys were administered each morning and evening using the Expiwell application on their phones (Tay & Pineda, 2020). These surveys were designed to gather subjective data on job stress, work engagement, and control measures such as sports centrality, frustration resilience, and persistence. The combination of objective sleep data with subjective self-reports and control measures offers a comprehensive view of the athletes experiences and conditions.

## Findings

The results of our study provide compelling evidence that sleep significantly mediates the relationship between stress and engagement among professional handball players. Data collected through wearable technology, specifically Oura rings that monitor sleep patterns, and comprehensive surveys revealed a clear pattern: higher levels of stress correlated with poorer sleep quality, including reduced deep sleep and increased sleep latency. This deterioration in sleep quality, in turn, was strongly associated with lower levels of athlete engagement. Moreover, the analysis confirmed that when athletes experienced better sleep quality, the negative effects of stress on engagement were diminished. These findings highlight the critical role of sleep as a buffer in the stress-engagement connection, highlighting its importance as a target for interventions aimed at enhancing athlete well-being and optimizing performance.

## Theoretical contributions

This study advances the theoretical landscape by linking the Job Demands-Resources (JDR) model and the Effort-Recovery Model to clarify the pivotal role of sleep as a mediating factor between stress and engagement in high-performance sports settings. By empirically demonstrating how sleep quality can buffer the adverse effects of stress on athlete engagement, our research enriches existing discussions within sports psychology and organizational behavior. It provides an understanding of sleep's function as a vital personal resource that supports recovery and sustains engagement under stress.

## Practical implications

The findings of our study offer several practical implications for athletes, coaches, and sports teams, emphasizing the critical importance of prioritizing sleep as a key component of sports training and management strategies. First, our research suggests that athletes should be educated on the impact of stress on sleep and, subsequently, on their engagement and performance, advocating for the incorporation of sleep hygiene practices into their daily routines. Coaches and sports teams can play a significant role in this by providing resources and support for sleep monitoring and improvement, such as wearable sleep trackers and access to sleep specialists. Furthermore, the adoption of flexible training schedules that allow for adequate rest and recovery could help mitigate stress levels, thereby enhancing sleep quality and overall athlete engagement. By implementing these strategies, sports organizations can create an environment that not only boosts the well-being and performance of their athletes but also fosters a culture that values and promotes the essential role of sleep in achieving sporting excellence.
REFERENCES:

1. Åkerstedt, T. (2006). Psychosocial stress and impaired sleep. *Scandinavian journal of work, environment & health*, 32(6), 493-501.

2. Amaral, A. P., Soares, M. J., Pinto, A. M., Pereira, A. T., Madeira, N., Bos, S. C., ... & Macedo, A. (2018). Sleep difficulties in college students: The role of stress, affect and cognitive processes. *Psychiatry research*, 260, 331-337.

3. Arnal, P. J., Thorey, V., Ballard, M. E., Hernandez, A. B., Guillot, A., Jourde, H., ... & Sauvet, F. (2020). The Dreem Headband as an Alternative to Polysomnography for EEG Signal Acquisition and Sleep Staging. *Sleep*, bioRxiv, 662734.

4. Bakker, A. B., & Demerouti, E. (2007). The Job Demands-Resources model: State of the art. *Journal of Managerial Psychology*, 22(3), 309–328.

5. Barnes, C. M., Ghumman, S. & Scott, B. A. (2013). Sleep and organisational citizenship behavior: The mediating role of job satisfaction. *Journal of Occupational Health Psychology*, 18(1), 16–26.

6. Hektner, J. M., Schmidt, J. A., & Csikszentmihalyi, M. (2007). Experience Sampling Method: Measuring the Quality of Everyday Life. Sage Publications.

7. Tay, L., Pineda, O. (2020). ExpiWell. http://www.expiwell.com

8. Walsh, N. P., Halson, S. L., Sargent, C., Roach, G. D., Nédélec, M., Gupta, L., ... & Samuels, C. H. (2021). Sleep and the athlete: narrative review and 2021 expert consensus recommendations. *British journal of sports medicine*, 55(7), 356-368.

9. Watson, A. M. (2017). Sleep and athletic performance. *Current sports medicine reports*, 16(6), 413-418.
TITLE: UNDERSTANDING THE INTERPLAY OF MEANINGFUL AND MEANINGLESS WORK

Blaž Abe

PhD student, University of Ljubljana, SEB

Keywords: meaningful work, meaningfulness, meaningless work, meaninglessness, organizational behavior, organizational psychology, existential psychology

Work has always been an important activity that defines our living. The concept of vocation and the idea that one is called to do a specific kind of work meant that occupations defined people, hence many surnames still refer to the work people have done, e.g., Smith – a person who works with metal (Standing, 2010). We still dedicate a significant portion of our lives to work, the significance of work therefore plays a vital role in evaluating the overall meaning of our lives (Ward & King, 2017). In the last century, however, significant changes have occurred in terms of how we work, where we work, and when we work (Borman, Ilgen & Klimoski, 2003). The cultivation of meaningful work has become even more evident with the covid crisis followed by the great resignation and quiet quitting, which show that people demand purpose and seek meaningful work (Ünal, 2022). Furthermore, recent technological advancements, especially the increasing use of artificial intelligence (AI) in the workplace, initiate the question of how the new technologies promote or diminish the experience of meaningful human work (Bankins & Formosa, 2023). A high percentage of dissatisfied individuals in the workplace can serve as a sign that it might be more beneficial to pay attention to understanding meaninglessness rather than reinforcing meaningfulness. Especially because people tend to discover a sense of meaningfulness on their own, while meaninglessness is fueled by leaders and organizations (Bailey & Madden, 2016).

In the field of meaning of work, there are many misconceptions, disagreements and paradoxes (Bailey & Madden, 2019), which are no help in creating more meaningful work at the workplace. It is faced with oversimplification and a lack of coherent identity (Rosso, Dekas, & Wrzesniewski, 2010). If we focus on meaninglessness, we can observe that, unlike meaningfulness, it is much less explored. This concept is given significantly less attention and is poorly defined, with empirical research being even more scarce, mainly undertaken by researchers Bailey and Madden (2016, 2017, 2019). Given the increasing popularity of the meaning of work, it would be necessary for a comprehensive understanding of the topic to delve into the interplay of meaningful work and meaningless work and which factors influence meaninglessness at work.

My research will be focused on discovering what makes work meaningful or meaningless, and specifically, what factors dictate it. The way we work has changed in the last decade, significantly in the last few years due to the pandemic and will presumably shift even more rapidly due to current technological advances. The goal is to gain an understanding of how to protect oneself from the rise of meaninglessness, not just attempting to ensure a higher level of meaningfulness, which, according to some findings, can be futile (Lips-Wiersma & Morris, 2009) or even harmful (Bailey et al., 2017). Some authors have called for more empirical research in the field of meaningful work (2019a).
On the other hand, this is a response to the call by Lips-Wiersma and Morris (2009) and Lips-Wiersma and Wright (2012), who emphasize the need for more research in the field of meaninglessness. In my research, I will focus on both quantitative and, especially, qualitative aspects since positivistic perspectives dominate this field (Bailey et al., 2019a). While the quantitative approach offers greater generalizability, qualitative research delves into personal experiences and individual narratives, leading to a more comprehensive understanding of the phenomenon (Johnson & Onwuegbuzie, 2004). In my study, I will give equal importance to the domain of meaninglessness as to meaningfulness at least, as current scholarship often neglects the negative side of it - meaninglessness.

One of my research goals is to develop a quantitative measurement scale for meaninglessness at work. To the best of my knowledge, such a scale does not currently exist. This could provide an entirely new dimension to understanding meaninglessness, which is often cited as the opposite of meaningfulness, although it is not well-explored how it relates to meaningfulness. Bailey and Madden (2016), in their empirical research, found that the factors contributing to meaningfulness and meaninglessness differ.

For that reason, we created a questionnaire using existing scales to measure meaningful work, meaningful life, meaninglessness in life and work, life satisfaction, organizational withdrawal, and other relevant demographics and basic work information. In the first step, the questionnaire on meaninglessness in work is simply a redesign of the measure for meaninglessness in life. Based on results from this study, we will gain insight into the interplay between meaningfulness and meaninglessness. We expect a negative correlation between meaningless and meaningful work. This will be followed by the second phase of data collection, where the newly established measurement scale will be tested alongside other relevant factors and their spectra.

In March 2024, data for the empirical hypotheses test were collected from a wide range of industries and workplaces, namely manufacturing and production, computer agents and IT section, managers, and finance agents in Montenegro.
## REFERENCES

1. Bailey, C., & Madden, A. (2016). What makes work meaningful—Or meaningless. MIT Sloan management review, 57(4), 1-9.

2. Bailey, C., & Madden, A. (2017). Time reclaimed: temporality and the experience of meaningful work. Work, employment and society, 31(1), 3-18.

3. Bailey, C., & Madden, A. (2019). “We’re not scum, we’re human”: Agential responses in the face of meaningless work. Scandinavian Journal of Management, 35(4), 101064.

4. Bankins, S., & Formosa, P. (2023). The ethical implications of artificial intelligence (AI) for meaningful work. Journal of Business Ethics, 1-16.

5. Borman, W. C., Ilgen, D. R., & Klimoski, R. J. (2003). Handbook of psychology: Industrial and organizational psychology, Vol. 12. John Wiley & Sons Inc.

6. Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational researcher, 33(7), 14-26.

7. Lips-Wiersma, M., & Morris, L. (2009). Discriminating between ‘meaningful work’ and the ‘management of meaning’. Journal of business ethics, 88, 491-511.

8. Lips-Wiersma, M., & Wright, S. (2012). Measuring the meaning of meaningful work: Development and validation of the Comprehensive Meaningful Work Scale (CMWS). Group & Organization Management, 37(5), 655-685.

9. Standing, G. (2010). Work after globalization: Building occupational citizenship. Cheltenham, UK and Northampton, MA: Edward Elgar Publishing.

10. Ünal, Z. M. (2022). Future of work: Designing meaningful work under the new era of COVID-19. In Handbook of research on future of work and education: Implications for curriculum delivery and work design (pp. 27-54). IGI Global.

11. Ward, S. J., & King, L. A. (2017). Work and the good life: How work contributes to meaning in life. Research in Organizational Behavior, 37, 59-82.
# THE DUAL ROLE OF PRICE IN CONSUMER DECISION-MAKING

**Marina Petrović**

marina.petrovic@ekof.bg.ac.rs

University of Belgrade, Faculty of Economics and Business, Belgrade

**Lazar Čolić**

lazar.colic@ekof.bg.ac.rs

University of Belgrade, Faculty of Economics and Business, Belgrade

Presenting author: Marina Petrović, PhD student

## ABSTRACT

**Theoretical background:** The decision-making process regarding product pricing and the formation of a pricing strategy is crucial for managers. Classical economics assumes that consumers make rational decisions, meaning that a price increase will lead to a decrease in demand. However, there is evidence of a paradox when it comes to consumers' perception of price in the process of making a purchase decision. This is because price serves two opposing roles in the consumer decision-making process (Bornemann & Homburg, 2011; Chang, 2013; Rao & Monroe, 1989; Sungjee Choi, 2022; Völckner, 2008).

There are two basic roles of price. The first is the “sacrifice effect”, which represents the traditional view of the consumer as a rational actor where the price represents the loss of money to obtain a product or service that would satisfy the consumer’s needs. In this case, the relationship is negative: higher prices lead to lower demand.

The second role is the “informational effect” which represents the price as an indicator of product quality. Consumers often infer the quality of a product based on its price, where higher prices indicate higher perceived quality. Therefore, the relationship is positive: higher prices lead to higher demand for that product.

However, it's important to note that the impact of this paradox can vary depending on various factors such as the type of product, the target market, and the overall positioning of the brand. Therefore, understanding this paradox and its implications is crucial for an effective pricing strategy.

Many researchers focus their work on the dual role of price in consumer decision-making, but they approach the topic from different perspectives and contexts. Bornemann & Homburg (2011) propose that psychological distance alters the weight consumers attach to the opposing roles of price. They show that from both a temporally and a socially distant perspective, the price-perceived quality relationship is more pronounced, while from a temporally proximal perspective, the price-perceived sacrifice relationship is more pronounced.

Chang (2013) demonstrates that consumers with high retrieval and processing fluency are more likely to evaluate price according to its implications for perceived quality and less likely to focus on price-perceived monetary sacrifice. Conversely, consumers with low retrieval and processing fluency are more likely to evaluate price according to its implications for monetary sacrifice and less likely to focus on price-perceived quality.
Sungjee Choi's (2022) study reassesses the price sensitivity theory and examines price's dual roles in consumers' decision-making processes: as a constraint and as a quality cue. It argues that consumers react more to high-priced products' price changes than to low-priced products' price change.

Tuzovic & Batt (2019) investigate the effects of price changes on purchase intentions for two products: wine (hedonic) versus laptop cases (utilitarian). The results indicate that price effects vary depending on the product category. Specifically, the influence of price increases for hedonic products is opposite to that for utilitarian products.

In summary, while all these papers discuss the dual role of price (as a measure of sacrifice and as an informational cue), they differ in the specific aspects they focus on, such as the influence of psychological distance, processing fluency, product type (hedonic vs. utilitarian), and price sensitivity.

**Purpose of study:** For managers in organizations who make decisions related to pricing strategy, it is crucial to be familiar with the dual role of price (Tuzovic & Batt, 2019). This dual role can be confirmed from various aspects, as presented in the theoretical background. These aspects may include price level, product type, psychological distance, or high retrieval and processing fluency. This study aims to empirically confirm the dual effect of price depending on the price level.

**Method:** An empirical research study was conducted to confirm the dual role of price based on different price levels. The data collection and analysis were performed using the Conjoint.ly survey research platform. The initial study was conducted on a convenience sample of 170 students from the University of Belgrade. Based on the conducted conjoint analysis, consumer utilities were obtained for choosing espresso coffee with various attributes and price levels.

**Findings:** The research results are depicted in Figure 1. Specifically, there is an increase in consumers' part-worth utility when it comes to purchasing espresso coffee as the price rises from 80 Serbian dinars (RSD) to 105 RSD. This price of 105 RSD represents an approximate estimated threshold below which the informational effect dominates, indicating that price serves as an indicator of quality. For values above 105 RSD, the utility function has a negative slope, indicating the dominance of the sacrifice effect. In other words, as the price increases, utility decreases because consumers need to sacrifice a larger amount of money to satisfy their needs.
<figure><img src="image_24.png" /><figcaption>**Figure 1:** Part-worth utilities for different price levels</figcaption></figure>

**Practical implications:** Managers need to understand that price plays a dual role in consumer decision-making - as a measure of sacrifice and as an informational cue. This understanding can help managers make more informed pricing decisions. Our research confirms that the effects of price changes depend on price level, so managers should consider this when setting prices for products.

In summary, this study suggests that pricing strategy should not be a one-size-fits-all approach. Instead, it should be tailored to the specific context, taking into account factors such as psychological distance, processing fluency, product type, price sensitivity and price level.

**Key words:** pricing, consumer behaviour, conjoint analysis

References

1. Bornemann, T., & Homburg, C. (2011). Psychological Distance and the Dual Role of Price. *Journal of Consumer Research, 38*(3), 490–504. https://doi.org/10.1086/659874

2. Chang, C.-J. (2013). Price or quality? The influence of fluency on the dual role of price. *Marketing Letters, 24*(4), 369–380. https://doi.org/10.1007/s11002-013-9223-8

3. Rao, A. R., & Monroe, K. B. (1989). The Effect of Price, Brand Name, and Store Name on Buyers' Perceptions of Product Quality: An Integrative Review. *Journal of Marketing Research, 26*(3), 351. https://doi.org/10.2307/3172907

4. Sungjee Choi. (2022). *Dual Role of Price in Consumer Choice: As a Constraint and as a Quality Cue*. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4232546

5. Tuzovic, S., & Batt, V. (2019). Investigating the Dual Role of Price on Consumers' Purchase Intentions of Hedonic versus Utilitarian Products: An Abstract (pp. 907–908). https://doi.org/10.1007/978-3-030-02568-7_255

6. Völckner, F. (2008). The dual role of price: decomposing consumers' reactions to price. *Journal of the Academy of Marketing Science, 36*(3), 359–377. https://doi.org/10.1007/s11747-007-0076-7
Soroush Dehghan Salmasi (Corresponding author)

Master Student

School of Economics and Business, University of Ljubljana Kardeljeva ploščad 17, 1000 Ljubljana,
Slovenia [Sd33521 @student.uni-lj.si](mailto:Sd33521@student.uni-lj.si)

T: +98 912 501 6501

Hossein Sharif (Dr.)

Senior Lecturer in AI & FinTech

School of Science & Technology Engineering (SST), City, University of London Northampton
Square, London EC1V 0HB

[Hossein.sharif@city.ac.uk](mailto:Hossein.sharif@city.ac.uk) T: +44 020 7040 4963

Mojca Indihar Štemberger (Dr.)

Full Professor

School of Economics and Business, University of Ljubljana Kardeljeva ploščad 17, 1000 Ljubljana,
Slovenia [Mojca.stemberger@ef.uni-lj.si](mailto:Mojca.stemberger@ef.uni-lj.si)

T: +386 1 5892-504

The incorporation of Artificial Intelligence (AI) into Human Resource Management (HRM) processes promises a new wave of innovation and invention (Zhou et al., 2023). At the same time, it presents a variety of paradoxical challenges in various domains such as legal, ethical and operational (Tambe et al., 2019). This study investigates the effectiveness of authentic leadership in mitigating these paradoxical challenges across four key HRM processes: Talent Acquisition, Performance Management, Training and Development, and Workplace Diversity and Inclusion. Authentic leaders, who possess qualities such as self-awareness, honesty, commitment to fairness, and transparency (Walumbwa et al., 2008), have the ability to more effectively address the AI- generated complexities and paradoxical challenges within HRM practices by employing various strategies (Kelly, 2023).

In talent acquisition, new AI-driven approaches and tools offer improved efficiencies through automation of resume screening (Black & van Esch, 2020) and identification of candidates that most closely align with the job requirements (Zhou et al., 2023). Nevertheless, this could potentially result in the standardization of the selection process to such a degree that it overlooks the distinctive qualitative elements of candidates' profiles that could render them an ideal match for the specific team dynamics or organizational culture. Authentic leaders are better posed to push for transparency and bias reduction in the use of AI tools for recruitment purposes. They accomplish this by suitably incorporating human-led interviews and interactions in the selection process. They ensure regular auditing of AI tools and algorithms for fairness and provide candidates and recruitment staff with the opportunity to offer feedback, thereby promoting ongoing improvement and recalibration (Walumbwa et al., 2008).

In performance management, there is a growing interest in AI-driven tools that offer exceptional breadth when it comes to monitoring and evaluating numerical and visible aspects of employee performance (Leicht-Deobald et al., 2022). However, these tools underperform dramatically in taking into account more subtle factors of employee performance (Tambe et al., 2019), including creativity, teamwork, leadership attributes and emotional intelligence. These aspects are more challenging to quantify or digitalize but play a vital role in the achievement of organizational objectives. While benefiting from the advantages of these AI tools, authentic leaders ensure incorporation of human feedback and insight. The process may entail the use of AI to identify patterns or identify areas that require enhancement.
However, the ultimate evaluation and formulation of development strategies are entrusted to human managers who possess a comprehensive and holistic understanding of an employee's overall performance advocating ethical and empathetic interpretation of AI output (Walumbwa et al., 2008).

In training and development, AI tools facilitate the implementation of training programs on a large scale. This is achieved by utilizing adaptive learning platforms that can personalize the learning experience for individuals. These platforms have the capability to adjust the content of the training according to the progress and performance of individual employees (Maity, 2019).

The pitfall here is a push towards isolated learning depriving the individual of the motivation, enjoyment and long term benefits of learning as a member of a cohesive group with shared values, goals and challenges. Authentic leaders while using AI tools to create personalized learning paths for employees, do not neglect the group and community aspects of learning that give it meaning, motivation and connection. This approach promotes a culture of collaborative learning through mentorship programs, peer learning groups, and cross-functional forums emphasizing human aspects of learning and growth (Walumbwa et al., 2008).

AI tools in diversity and inclusion initiatives aim to detect discrimination and favouritism in HRM processes such as recruitment and promotion. On the other hand, there is now growing body of evidence that AI systems (Raghavan et al., 2020 ; Ore & Sposato, 2022), particularly those using novel generative AI approaches, suffer from inherent biases due to data they are trained on and/or deficiencies in their architecture and algorithms. This not only could lead to underperformance in detecting discrimination and favouritism, but could in fact accentuate existing problems in this context. Authentic leaders would not fully outsource supervision and monitoring of crucial HRM processes such as recruitment and promotion to current AI tools with known deficiencies and shortcomings.

Table 1 compares more and less Authentic leaders' responses to AI's paradoxical problems in HRM processes:
<table><caption>Table 1. Authentic leadership and AI-related paradoxical problems in HRM</caption><thead><tr><td>HRM Process</td><td>A More Authentic Leadership Approach</td><td>A Less Authentic Leadership Approach</td></tr></thead><tbody><tr><td>Talent Acquisition</td><td>Emphasizes a balanced utilization of AI to optimize efficiency, while also ensuring that human judgment remains integral in making final judgments. The primary emphasis is on using ethical AI practices to improve fairness in the recruiting process.</td><td>Heavily depends on AI to make decisions, with little human supervision, sometimes disregarding the subtleties of cultural compatibility and unquantifiable characteristics.</td></tr><tr><td>Performance Management</td><td>Utilizes AI to facilitate the provision of data-driven insights; however, it emphasizes the necessity of human interpretation and context, thereby advocating for a comprehensive assessment of employee performance that encompasses subjective inputs.</td><td>Relies heavily on AI-generated data for performance assessments, sometimes overlooking intangible accomplishments like mentoring colleagues or improving cohesiveness among team members.</td></tr><tr><td>Training and Development</td><td>Employs AI to create customized learning experiences while simultaneously promoting interpersonal connections through mentoring and collaborative learning, assuring that they are in line with individual professional objectives.</td><td>Leans on AI-driven training programs, diminishing the significance of peer learning environments, such as in-person training sessions, where employees have the opportunity to learn from one another's viewpoints and experiences, fostering a sense of solidarity and promoting teamwork.</td></tr><tr><td>Workplace Diversity and Inclusion</td><td>Diligently examines AI tools for potential bias and advocates for their utilization in complementing, rather than supplanting, diversity initiatives led by humans. This underscores the significance of human discernment and empathy.</td><td>Implements AI technologies in diversity initiatives without giving enough consideration to the possibility of prejudice or the reinforcement of existing inequalities, ignoring the human aspect of inclusion.</td></tr></tbody></table>

This study argues that authentic leaders are crucial in harnessing the full potential of current AI tools in HRM, while putting into action processes, tactics and tools that avoid or reduce potential paradoxical problems associated with a fully AI-driven approach. Authentic leaders can more effectively use AI tools to support corporate objectives while upholding ethical norms and preserving the inherent value of human insight and judgment. This requires a mix of strategic vision, ethical monitoring, and a strong dedication to the human aspects of HR.

References

1. Black, J. S., & van Esch, P. (2020). AI-enabled recruiting: What is it and how should a manager use it? *Business Horizons*, *63*(2), 215-226.
https://doi.org/10.1016/j.bushor.2019.12.001

2. Kelly, L. (2023). *Artificial Intelligence and Authentic Leadership.* "Mindfulness for Authentic Leadership: Theory and Cases*. (pp. 227-258). Cham: Springer International Publishing.
https://doi.org/10.1007/978-3-031-34677-4_14

3. Leicht-Deobald, U., Busch, T., Schank, C., Weibel, A., Schafheitle, S., Wildhaber, I., & Kasper,

4. G. (2022). The challenges of algorithm-based hr decision-making for personal integrity. *Business and the Ethical Implications of Technology*, *160*(2), 71-86.
https://doi.org/10.1007/s10551-019-04204-w

5. Maity, S. (2019). Identifying opportunities for artificial intelligence in the evolution of training and development practices. *Journal of Management Development*, *38*(8), 651-663.
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