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Purpose
The authors study the valuation effect of corporate diversification in the initial phase of the COVID-19 pandemic in 2020 in Europe.
Design/methodology/approach
Applying a cross-sectional regression model to a sample of public companies headquartered in the European Union, the authors investigate the existence of and the change in a diversification discount between 2018 and 2020. By applying the Excess Q methodology, the authors make an industry adjustment of diversified companies to measure the value effect of corporate diversification.
Findings
The authors find an economically and statistically significant diversification discount that increases from an average Excess Q of −0.05 in 2019 to −0.10 in 2020. The diversified companies' inferior fundamental financial performance in 2020 accompanies the discount. The results deviate from those of previous research, which mostly show a decrease in the diversification discount in economic crises, and thereby, shed doubt on whether diversification provides insurance against pandemic-induced adverse value effects.
Originality/valueThe study distinguishes the role of corporate diversification during recessionary periods by establishing that the valuation effect of diversification depends on the nature of the crisis. The analysis incorporates criticism of previous studies concerning a biased methodology and uniform data source by applying the Excess Q methodology and using FactSet industry segment data.
Purpose – This paper explores, which employer attractiveness attributes Generation Z (Gen Z) talents prioritize. Comparing the findings for female and male participants, this study examines whether gender-specific work value orientations prevail among Gen Z talents and impact their expectations toward employers.
Design/methodology/approach – A survey was conducted among 308 students of business, economics and management in Germany. Data were collected using the employer attractiveness scale of Berthon and colleagues (2005) complemented by an additional dimension focusing on work–life balance.
Findings – Findings indicate that Gen Z talents primarily expect a fun work environment, a positive team atmosphere and supportive relations with colleagues and superiors. Application aspects and work–life balance enabling services are expected the least. Expectations of four of the six attributes measured differ significantly among women and men, indicating that traditional gender assumptions continue to be reflected in the work value orientations of Gen Z talents.
Research limitations/implications – The sample was limited to business, economics and management students in Germany. Additional research should include a wider variety of respondents of different disciplines and countries.
Practical implications – Practical implications refer to emphasizing the social value of employment in the employee value proposition and customizing employer branding activities by gender.
Originality/value – This study contributes to the literature by empirically determining which employer attractiveness attributes Gen Z talents expect and whether and how these expectations vary by gender.
Purpose
In recognising the key role of business intelligence and big data analytics in influencing companies’ decision-making processes, this paper aims to codify the main phases through which companies can approach, develop and manage big data analytics.
Design/methodology/approach
By adopting a research strategy based on case studies, this paper depicts the main phases and challenges that companies “live” through in approaching big data analytics as a way to support their decision-making processes. The analysis of case studies has been chosen as the main research method because it offers the possibility for different data sources to describe a phenomenon and subsequently to develop and test theories.
Findings
This paper provides a possible depiction of the main phases and challenges through which the approach(es) to big data analytics can emerge and evolve over time with reference to companies’ decision-making processes.
Research limitations/implications
This paper recalls the attention of researchers in defining clear patterns through which technology-based approaches should be developed. In its depiction of the main phases of the development of big data analytics in companies’ decision-making processes, this paper highlights the possible domains in which to define and renovate approaches to value. The proposed conceptual model derives from the adoption of an inductive approach. Despite its validity, it is discussed and questioned through multiple case studies. In addition, its generalisability requires further discussion and analysis in the light of alternative interpretative perspectives.
Practical implications
The reflections herein offer practitioners interested in company management the possibility to develop performance measurement tools that can evaluate how each phase can contribute to companies’ value creation processes.
Originality/value
This paper contributes to the ongoing debate about the role of digital technologies in influencing managerial and social models. This paper provides a conceptual model that is able to support both researchers and practitioners in understanding through which phases big data analytics can be approached and managed to enhance value processes.
Purpose
Job advertisements are important means of communicating role expectations for management accountants to the labor market. They provide information about which roles are sought and expected. However, which roles are communicated in job advertisements is unknown so far.
Design/methodology/approach
With a text-mining approach on a large sample of 889 job ads, the authors extract information on roles, type of firm and hierarchical position of the management accountant sought.
Findings
The results indicate an apparent mix of different role types with a strong focus on a classic watchdog role. However, the business partner role is more often sought for leadership positions or in family businesses and small- and medium-sized enterprises (SME).
Research limitations/implications
The main limitation is the lack of an agreed-upon measurement instrument for roles in job offers. The study results imply that corporate practice is not as theory-driven as is postulated and communicated in the management accounting community. This indicates the existence of a research-practice gap and tensions between different actors in the management accounting field.
Practical implications
The results challenge the current role discussion of professional organizations for management accountants as business partners.
Originality/value
The authors contribute the first study, which explicitly analyzes the communication of roles in job offers for management accountants. It indicates a discrepancy between scholarly discussion on roles and management accountants' work from an employer's perspective.
Purpose
Digital transformation of organizations has major implications for required skills and competencies of the workforce, both as a prerequisite for implementation, and, as a consequence of the transformation. The purpose of this study is to analyze required skills and competencies for digital transformation using the context of robotic process automation (RPA) as an example.
Design/methodology/approach
This study is based on an explorative, thematic coding analysis of 119 job advertisements related to RPA. The data was collected from major online job platforms, qualitatively coded and subsequently analyzed quantitatively.
Findings
The research highlights the general importance of specific skills and competencies for digital transformation and shows a gap between available skills and required skills. Moreover, it is concluded that reskilling the existing workforce might be difficult. Many emerging positions can be found in the consulting sector, which raises questions about the permanent vs temporary nature of the requirements, as well as the difficulty of acquiring the required knowledge.
Originality/value
This paper contributes to knowledge by providing new empirical findings and a novel perspective to the ongoing discussion of digital skills, employment effects and reskilling demands of the existing workforce owing to recent technological developments and automation in the overall context of digital transformation.