Search results
1 – 8 of 8Catherine Needham, Sharon Mastracci and Catherine Mangan
Within public services there is a widely recognised role for workers who operate across organisational and professional boundaries. Much of this literature focusses on the…
Abstract
Purpose
Within public services there is a widely recognised role for workers who operate across organisational and professional boundaries. Much of this literature focusses on the organisational implications rather than on how boundary spanners engage with citizens. An increased number of public service roles require boundary spanning to support citizens with cross-cutting issues. The purpose of this paper is to explicate the emotional labour within the interactions that boundary spanners have with citizens, requiring adherence to display rules and building trust.
Design/methodology/approach
This is a conceptual paper which draws on illustrative examples to draw out the emotional labour within two types of boundary spanning: explicit and emergent.
Findings
Emotional labour theory offers a way to classify these interactions as requiring high, medium or low degrees of emotional labour. Boundary spanning theory contributes an understanding of how emotional labour is likely to be differently experienced depending on whether the boundary spanning is an explicit part of the job, or an emergent property.
Originality/value
Drawing on examples from public service work in a range of advanced democracies, the authors make a theoretical argument, suggesting that a more complete view of boundary spanning must account for individual-level affect and demands upon workers. Such a focus captures the “how” of the boundary spanning public encounter, and not just the institutional, political and organisational dimensions examined in most boundary spanning literatures.
Details
Keywords
Kristi Stiles, Yesenia Lopez, Samantha Tung and J. Abuda
Abstract
Details
Keywords
Theresa Eriksson, Alessandro Bigi and Michelle Bonera
This paper explores if and how Artificial Intelligence can contribute to marketing strategy formulation.
Abstract
Purpose
This paper explores if and how Artificial Intelligence can contribute to marketing strategy formulation.
Design/methodology/approach
Qualitative research based on exploratory in-depth interviews with industry experts currently working with artificial intelligence tools.
Findings
Key themes include: (1) Importance of AI in strategic marketing decision management; (2) Presence of AI in strategic decision management; (3) Role of AI in strategic decision management; (4) Importance of business culture for the use of AI; (5) Impact of AI on the business’ organizational model. A key consideration is a “creative-possibility perspective,” highlighting the future potential to use AI not only for rational but also for creative thinking purposes.
Research limitations/implications
This work is focused only on strategy creation as a deliberate process. For this, AI can be used as an effective response to the external contingencies of high volumes of data and uncertain environmental conditions, as well as being an effective response to the external contingencies of limited managerial cognition. A key future consideration is a “creative-possibility perspective.”
Practical implications
A practical extension of the Gartner Analytics Ascendancy Model (Maoz, 2013).
Originality/value
This paper aims to contribute knowledge relating to the role of AI in marketing strategy formulation and explores the potential avenues for future use of AI in the strategic marketing process. This is explored through the lens of contingency theory, and additionally, findings are expressed using the Gartner analytics ascendancy model.
Details
Keywords
Erica Poma and Barbara Pistoresi
This paper aims to appraise the effectiveness of gender quotas in breaking the glass ceiling for women on boards (WoBs) in companies that are legally obliged to comply with quotas…
Abstract
Purpose
This paper aims to appraise the effectiveness of gender quotas in breaking the glass ceiling for women on boards (WoBs) in companies that are legally obliged to comply with quotas (listed companies and state-owned companies, LP) and in those that are not (unlisted companies and nonstate-owned companies, NLNP). Furthermore, it investigates the glass cliff phenomenon, according to which women are more likely to be appointed to apical positions in underperforming companies.
Design/methodology/approach
A balanced panel data of the top 116 Italian companies by total assets, which are present in both 2010 and 2017, is used for estimating ANOVA tests across sectors and fixed-effects panel regression models.
Findings
WoBs significantly increased in both the LP and the NLNP companies, and this increase was greater in the financial sector. Furthermore, the relationship between the percentage of WoBs and firm performance is not linear but depends on the financial corporate health. Specifically, the situation in which a woman ascends to a leadership position in challenging circumstances where the risk of failure is high (glass cliff phenomenon) is only present in companies with the lowest performance in the sample, in other words, when negative values of Roe and negative or zero values of Roa occur together.
Practical implications
These findings have relevant policy implications that encourage the adoption of gender quotas even in specific top positions, such as CEO or president, as this could lead to a “double spillover effect” both vertically, that is, in other job positions, and horizontally, toward other companies not targeted by quotas. Practical interventions to support women in glass cliff positions, on the other hand, relate to the extent of supervisor mentoring and support to prevent women from leaving director roles and strengthen their chances for career advancement.
Originality/value
The authors explore the ability of gender quotas to break through the glass ceiling in companies that are not legally obliged to do so, and to the best of the authors’ knowledge, for the first time, the glass cliff phenomenon in the Italian context.
Details