Samenvatting artikelen Strategisch HRM
Week 2
Blom et al. (2018)
One HRM fits all? A meta-analysis of the effects of HRM practices in the Public, Semi-
public and private sector
This article is about an analyses with the ability-motivation-opportunity (AMO) model on the
differences in the effects of HRM practices between the private and public sector. Significant
differences exist, but they are not straightforward. According to the AMO model, to enhance
individual performance, HRM practices should be designed to enhance an employee’s ability,
motivation and opportunity to perform. Individual performance is defined in terms of behaviours
and actions that have an impact on the organizations goals and are under the control of the
individual. There is in-role performance (what you were hired to do) and extra-role performance
(beyond the call of duty).
With the AMO model, HRM tactics are increasing knowledge/skills (ability enhancing),
increasing motivation through performance management or internal promotion opportunity
(motivation enhancing), and employee participation and empowerment (opportunity
enhancing). In the public sector, ability enhancing was very effective, whereas motivation
enhancing lowered job satisfaction/was weaker. The public sector is different. This has several
explanations.
First, there is organizational goal ambiguity. The goals are not very defined or clear in
PA. This means goal-focused HRM tactics are less effective. This is hypothesized to be more
so in the public sector than in the semi-public sector, in which organizations are often created
for one goal. Secondly, there is formal personnel constraints. Because of the political
accountability there are often (external) control groups or certain rules. This means public
managers difficulty implementing certain HRM practices; they have less freedom and power
to manage their employees than private managers. Third, there is employee motivation or
public sector motivation. The specific norms and values and intrinsic (and altruistic) motivation
that drive civil servants can hinder certain HRM practices.
The hypothesis are that the effects of ability-enhancing, motivation-enhancing, and
opportunity-enhancing HRM practices are larger in the semi-public sector than in the public
sector, and smaller than in the private sector. Statistics is used.
The study found that ability-enhancing and opportunity-enhancing HRM tactics on in-
role performance had a significant effect in the private and semi-public sector. No significant
effect is found for motivation-enhancing practices.
For extra-role performance, ability-enhancing and opportunity-enhancing tactics were
significant in each sector, the most in the semi-public sector. Concerning motivation-
enhancing, it was only significant in the private and public sector.
The difference between sectors is smaller than hypothesised. An explanation could be that
other factors like organizational size or culture are more key to the possible effect of those
HRM strategies than the sector.
There was strong effect of opportunity-enhancing practices for extra-role performance
in the semi-public sector which can be explained because the employees there are
professionals with specialized knowledge and high intrinsic motivation, like doctors. In the
public sector, managers have more red tape in this regard and thus the employees less
autonomy.
, For the motivation-enhancing, there is a mismatch between the extrinsic focused
motivation-enhancing practices and the intrinsic motivation of people working in the
(semi)public sector. Furthermore, for in-role performance, ability-enhancing is less effective or
needed because of the high initial expertise.
The flaws in this article are that the correlation between HRM practices and individual
performance can be overrated because there is no consideration of other factors like
organization size of culture. There is also no attention to culture or social factors. Also, semi-
public organizations were defined here as health and education, while this area is broader in
truth (non profit organizations).
Van den Heuvel & Bondarouk (2017)
The rise (and fall?) of HR analytics
A study into the future application, value, structure, and system support
HR analytics began as an information system in the 1980s. By the 2000s, it had in cooperated
many technological developments and ‘e-HRM’ came into existence, like talent acquisition
services. Today, our lives revolve more and more around data, and personnel management is
often digitized. HR professionals can now choose to use data to support decision making about
human capital. The research question is: what will HR analytics look like in 2025 in terms of its
application, value, structure, and system support?
HR analytics is defined as the systematic identification and quantification of the HR-
drives of business outcomes with the purpose of making better decisions. HR analytics in
businesses nowadays is not a well-developed field, and this is also true for the scientific field.
The authors argue, however, that HR analytics may enable large changes in HRM function
and that technologies evolve rapidly.
Organizations try to move towards predictive HR analytics. For this not only data and
analysis is needed, but also logic models to understand them and other things like a good
positioning of the HR department in a organization, and combining of different perspectives.
The multidimensional perspective adapted in this article has four central topics from which they
study the future of HR analytics:
1) Application (goals, problems, challenges of an application)
The application of HR analytics (HRA) in 2015 is seen in goals, current analytical focus, and
current themes. The goal right now is to set up HRA and proving its value – but also
researching its applications and value. The current analytical focus of HRA is provide basic
reporting and calculating metrics (meetkunde). Its focus is historical insights, not predictive
analysis. The themes right now are exclusively HR themes.
The prediction of HRA application in 2025 is different. The goal was predicted to be
fostering fact-based organizational decision making; a more evidence-based mindset in HR
itself; and determining the HR drives of business outcomes; and balancing privacy and data.
The analytical focus was predicted to shift to predictive analytics and data integration with other
fields. The themes predicted were diverse: leadership, recruitment, planning, self-steering
teams, and more. The themes would not differ a lot but become more complex because they
would also use data from other fields.
2) Value (added value as seen by the organization, influence on decision making)
The value of HRA in 2015 is for many still unclear. This is a current challenge, for people to
take HRA seriously and adopt it in their decision making. In 2025, it is predicted to be an
established practice. The general trend towards evidence-based decision making helps this.
, 3) Structure (positioning, organization, involved actors)
The structure of HRA is about the positioning and organization of HRA. In 2015, it’s mostly
organized as a specialized team and positioned within the HR function. Connections between
the HR department and other departments is limited. The structure in 2025 is predicted to be
different. The positioning of HRA is debated to stay within HR, become integrated in an
organization-wide analytical team, or something in between. The internal actors involved will
be some HR specialists and some statistical specialists. They would be cooperating closely
with other departments and guided by the board and managers. Potential external actors like
educators or data providers could also be involved.
4) System support (from IT)
The system support of HRA in 2015 is considered limited. The current IT (lack of) support is
considered the biggest obstacle today. The right data is not always available. In 2025, IT is
predicted to be the main driver of HRA. One data-system for the whole organization and
automatic data collection are also mentioned. The IT support would also become analysing,
not only reporting.
The future of HRA will be driven by an emphasis on integration; integration of data from
different fields; integrated IT structure; and integration of governance of the various existing
analytics. Technology will develop and this will also drive HRA.
A limitation of this study is that is was conducted through researching HRA experts;
while they know a lot about their field, there is no perspective on how other fields and experts
view HRA. Furthermore, different kinds of organization may require different HRA. More
research is needed.
Week 3
Agarwal (2018)
Public Administration challenges in the world of AI and bots
Technology is changing more rapidly than ever before. Technology influencing both labour-
intensive and administrative jobs. Many lower-end jobs could be replaced by robots.
Public administration is reactive by nature; It is hard to tackle problems that do not exist
yet. However, the new wave of robot/AI/IoT technology poses a major challenge and a need
to act sooner rather than later. There is a need for the public sector to engage proactively.
This article foresees five primary challengers of public administrators:
1. The first is electronic government services, like voice enabling government services.
For this, professionals are needed that the government does not have. Productive
partnerships with the private sector could be formed, but could also lead to no control
on the governments part.
2. Job, economy, and social safety nets are the next challenges as many jobs fall away
and (older) people’s world gets turned upside down.
3. The third challenge is revenue shortfall, as taxes on oil or parking will lessen, as the
vehicle world will change. Taxing robots could be a solution.
4. Next, consumer protection will be a challenge. AIs will carry the biases of the data they
use to learn. Humans produce data, and humans are biased. AIs could even start to
amplify the bias. So there should be protection against that.
