Emotions & KM #emotions


Matt Moore
 

Hi,

So as you will have seen from Stan's email, I will be doing a session
on emotions and KM in later October.

I have started work on the presentation but I'd be interested to hear
thoughts from the community on this topic.

- How do KM and emotion inter-relate?
- What role do emotions (of ourselves, of others) play in the work that we do?
- How are different emotions bound up with knowledge and how do the
impact knowledge creation, knowledge dissemination, and knowledge use?

BTW emotions are a big part of being human but a literature search
reveals only about 10-20 articles on emotion and KM over the last 20
years.

Regards,
--
Matt Moore
M. +61 (0) 423 784 504
matt@innotecture.com.au


Murray Jennex
 

my journal has another KM and emotions article coming out in 2021


-----Original Message-----
From: Matt Moore <matt@...>
To: main@sikm.groups.io
Sent: Fri, Sep 25, 2020 4:33 pm
Subject: [SIKM] Emotions & KM

Hi,

So as you will have seen from Stan's email, I will be doing a session
on emotions and KM in later October.

I have started work on the presentation but I'd be interested to hear
thoughts from the community on this topic.

- How do KM and emotion inter-relate?
- What role do emotions (of ourselves, of others) play in the work that we do?
- How are different emotions bound up with knowledge and how do the
impact knowledge creation, knowledge dissemination, and knowledge use?

BTW emotions are a big part of being human but a literature search
reveals only about 10-20 articles on emotion and KM over the last 20
years.

Regards,
--
Matt Moore
M. +61 (0) 423 784 504
matt@...






John Lewis
 

Great questions about KM and emotions.
I will be presenting on Monday on Story Thinking and KM, and will also cover the common emotions throughout.
Here is the link for my presentation on Monday (10AM ET) for the Knowledge Management Institute:
https://us02web.zoom.us/meeting/register/tZYkcOioqj8oEt1eQbr2XNrYRPbaKstiHlaS
Please join us, and I look forward to following up with others that have this interest.

John Lewis, Ed.D.

On Fri, Sep 25, 2020 at 11:28 PM Murray Jennex via groups.io <murphjen=aol.com@groups.io> wrote:
my journal has another KM and emotions article coming out in 2021


-----Original Message-----
From: Matt Moore <matt@...>
To: main@sikm.groups.io
Sent: Fri, Sep 25, 2020 4:33 pm
Subject: [SIKM] Emotions & KM

Hi,

So as you will have seen from Stan's email, I will be doing a session
on emotions and KM in later October.

I have started work on the presentation but I'd be interested to hear
thoughts from the community on this topic.

- How do KM and emotion inter-relate?
- What role do emotions (of ourselves, of others) play in the work that we do?
- How are different emotions bound up with knowledge and how do the
impact knowledge creation, knowledge dissemination, and knowledge use?

BTW emotions are a big part of being human but a literature search
reveals only about 10-20 articles on emotion and KM over the last 20
years.

Regards,
--
Matt Moore
M. +61 (0) 423 784 504
matt@...






Matt Moore
 

What is it about and who is it by?

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 1:28 PM, Murray Jennex via groups.io <murphjen@...> wrote:


my journal has another KM and emotions article coming out in 2021


Murray Jennex
 

When Emotions Rule Knowledge: A Text-Mining Study of Emotions in Knowledge Management Research

Emotions are as much a part of human behavior as reason and play an important role in intelligence and knowledge (Martı́nez-Miranda & Aldea, 2005). Managing knowledge in organizations has proved to be very useful since successful knowledge management (KM) leads to significant improvements in their scientific, economic, and social aspects (Cao et al., 2012). Nonetheless, knowledge is often viewed merely as just another manageable organizational resource (Alavi & Leidner, 2001). Owing to its context-specificity and boundedness to human beings (Nonaka, 1994), however, it cannot be separated from human emotions and, thus, has to be approached differently than other organizational resources (Kuo et al., 2003). Consequently, the role played by emotions, which help to both express and understand knowledge (Davenport & Prusak, 1998), requires attention from within the information systems (IS) domain in general and from KM researchers in particular.
 
IS researchers have started to pay attention to the presence and role of emotions (Chau et al., 2020; Beaudry & Pinsonneault, 2010; Gregor et al., 2014). Likewise, KM studies on emotion-related topics are critical to acknowledging emotions and the role emotional concepts play in KM (Scherer & Tran, 2003; van den Hooff et al., 2012). Nonetheless, these studies also show how compartmentalized KM research on emotions is. It only focuses on single emotions and limited subtopics from emotion research while neglecting an overall and holistic perspective that would help to develop common ground in this area. For instance, concerning KM processes, the roles of emotional intelligence (Decker et al., 2009; Peng, 2013; Trong Tuan, 2013) and emotional obstacles (Lin et al., 2006; Pemberton et al., 2007) have been investigated. However, an integrated and comprehensive overview of emotions, unbiased by any particular single topic, is still lacking, and it is necessary to consolidate research on single emotions and emotional concepts (Hornung & Smolnik, 2018), and in which nexus they are displayed in KM research – with a taxonomy of emotions in KM research as the ultimate goal. To arrive at a comprehensive taxonomy of emotions in KM and close the aforementioned gap, it is crucial to understand which emotions are prevalent in and dominate KM research. Sentiment analyses, which have often been used to detect words associated with either positive or negative emotions in the context of politics, finance, and (social media) marketing (Matthies, 2016; Yassine & Hajj, 2010), are a useful instrument to gain a broader understanding of emotions. As a special type of text mining, sentiment analyses support the authors’ goal of analyzing the underlying sentiment of a text that “can encompass investigating both the opinion and the emotion behind that unit” (Yadollahi et al., 2017, p. 2). Sentiment analyses also enable the exploration of vast amounts of data. They are also effective at revealing which emotions prevail in written KM publications and can, therefore, help to answer the following research questions:
RQ1: Which emotions dominate research on KM?
RQ2: How can these emotions be categorized according to emotion scales?
The sentiment analysis in this study relies on a dictionary-based approach in which KM-specific dictionaries 1) are created based on Hu and Liu (2004) and 2) applied to a comprehensive sample of 6,017 scientific KM publications to detect existing emotions. The analysis results are then 3) categorized and structured using an appropriate emotion scale.

the corresponding author is Olivia Hornung, the lead author is Nora Fteimi and the 3rd author is Stefan Smolnik, they are from the universities of Hagen and Passau in Germany.  Stefan is a research partner of mine but this research comes from his research team at Hagen.....murray


-----Original Message-----
From: Matt Moore <matt@...>
To: main@sikm.groups.io
Sent: Fri, Sep 25, 2020 9:24 pm
Subject: Re: [SIKM] Emotions & KM

What is it about and who is it by?

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 1:28 PM, Murray Jennex via groups.io <murphjen@...> wrote:


my journal has another KM and emotions article coming out in 2021


Patrick Lambe
 

Matt - there’s more on emotions in the context of learning - “affect” is the term typically used.

Nate Allen (of Company Command fame) did a study with colleagues on the role of emotional affect in learning and leadership in crisis situations. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.845.7532&rep=rep1&type=pdf

George Mandler did a study on affect, problem solving and memory in the 1980s. The link is to an e-book on affect and mathematical problem solving (educational focus), Mandler's paper is chapter 1 https://d1wqtxts1xzle7.cloudfront.net/63633380/affect_and_mathematical_problem_solving20200615-98668-qo4e09.pdf

P



Patrick Lambe
Partner
Straits Knowledge

phone:  +65 98528511

web:  www.straitsknowledge.com
resources:  www.greenchameleon.com
knowledge mapping:  www.aithinsoftware.com


On 26 Sep 2020, at 12:36 PM, Murray Jennex via groups.io <murphjen@...> wrote:

When Emotions Rule Knowledge: A Text-Mining Study of Emotions in Knowledge Management Research

Emotions are as much a part of human behavior as reason and play an important role in intelligence and knowledge (Martı́nez-Miranda & Aldea, 2005). Managing knowledge in organizations has proved to be very useful since successful knowledge management (KM) leads to significant improvements in their scientific, economic, and social aspects (Cao et al., 2012). Nonetheless, knowledge is often viewed merely as just another manageable organizational resource (Alavi & Leidner, 2001). Owing to its context-specificity and boundedness to human beings (Nonaka, 1994), however, it cannot be separated from human emotions and, thus, has to be approached differently than other organizational resources (Kuo et al., 2003). Consequently, the role played by emotions, which help to both express and understand knowledge (Davenport & Prusak, 1998), requires attention from within the information systems (IS) domain in general and from KM researchers in particular.
 
IS researchers have started to pay attention to the presence and role of emotions (Chau et al., 2020; Beaudry & Pinsonneault, 2010; Gregor et al., 2014). Likewise, KM studies on emotion-related topics are critical to acknowledging emotions and the role emotional concepts play in KM (Scherer & Tran, 2003; van den Hooff et al., 2012). Nonetheless, these studies also show how compartmentalized KM research on emotions is. It only focuses on single emotions and limited subtopics from emotion research while neglecting an overall and holistic perspective that would help to develop common ground in this area. For instance, concerning KM processes, the roles of emotional intelligence (Decker et al., 2009; Peng, 2013; Trong Tuan, 2013) and emotional obstacles (Lin et al., 2006; Pemberton et al., 2007) have been investigated. However, an integrated and comprehensive overview of emotions, unbiased by any particular single topic, is still lacking, and it is necessary to consolidate research on single emotions and emotional concepts (Hornung & Smolnik, 2018), and in which nexus they are displayed in KM research – with a taxonomy of emotions in KM research as the ultimate goal. To arrive at a comprehensive taxonomy of emotions in KM and close the aforementioned gap, it is crucial to understand which emotions are prevalent in and dominate KM research. Sentiment analyses, which have often been used to detect words associated with either positive or negative emotions in the context of politics, finance, and (social media) marketing (Matthies, 2016; Yassine & Hajj, 2010), are a useful instrument to gain a broader understanding of emotions. As a special type of text mining, sentiment analyses support the authors’ goal of analyzing the underlying sentiment of a text that “can encompass investigating both the opinion and the emotion behind that unit” (Yadollahi et al., 2017, p. 2). Sentiment analyses also enable the exploration of vast amounts of data. They are also effective at revealing which emotions prevail in written KM publications and can, therefore, help to answer the following research questions:
RQ1: Which emotions dominate research on KM?
RQ2: How can these emotions be categorized according to emotion scales?
The sentiment analysis in this study relies on a dictionary-based approach in which KM-specific dictionaries 1) are created based on Hu and Liu (2004) and 2) applied to a comprehensive sample of 6,017 scientific KM publications to detect existing emotions. The analysis results are then 3) categorized and structured using an appropriate emotion scale.

the corresponding author is Olivia Hornung, the lead author is Nora Fteimi and the 3rd author is Stefan Smolnik, they are from the universities of Hagen and Passau in Germany.  Stefan is a research partner of mine but this research comes from his research team at Hagen.....murray


-----Original Message-----
From: Matt Moore <matt@...>
To: main@sikm.groups.io
Sent: Fri, Sep 25, 2020 9:24 pm
Subject: Re: [SIKM] Emotions & KM

What is it about and who is it by?

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 1:28 PM, Murray Jennex via groups.io <murphjen@...> wrote:


my journal has another KM and emotions article coming out in 2021


Matt Moore
 

Thanks Murray,

I have read the conference paper I think this research is based on - and a previous paper by Hornung & Smolnik. I’ll be incorporating some of both of them into my presso.

I think the earlier paper is a good literature review. My main issue with their approach is that they seem to be conducting purely secondary research - trying to mine the academic literature in ever more elaborate ways. I would like to see 1. more primary investigation and 2. more “so what”.

BTW one of the issues with the research on emotion in general (not just KM) is the dissonance between content & form. The writing is as bloodless as the topics are intense.

Regards,

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 2:36 PM, Murray Jennex via groups.io <murphjen@...> wrote:


When Emotions Rule Knowledge: A Text-Mining Study of Emotions in Knowledge Management Research

Emotions are as much a part of human behavior as reason and play an important role in intelligence and knowledge (Martı́nez-Miranda & Aldea, 2005). Managing knowledge in organizations has proved to be very useful since successful knowledge management (KM) leads to significant improvements in their scientific, economic, and social aspects (Cao et al., 2012). Nonetheless, knowledge is often viewed merely as just another manageable organizational resource (Alavi & Leidner, 2001). Owing to its context-specificity and boundedness to human beings (Nonaka, 1994), however, it cannot be separated from human emotions and, thus, has to be approached differently than other organizational resources (Kuo et al., 2003). Consequently, the role played by emotions, which help to both express and understand knowledge (Davenport & Prusak, 1998), requires attention from within the information systems (IS) domain in general and from KM researchers in particular.
 
IS researchers have started to pay attention to the presence and role of emotions (Chau et al., 2020; Beaudry & Pinsonneault, 2010; Gregor et al., 2014). Likewise, KM studies on emotion-related topics are critical to acknowledging emotions and the role emotional concepts play in KM (Scherer & Tran, 2003; van den Hooff et al., 2012). Nonetheless, these studies also show how compartmentalized KM research on emotions is. It only focuses on single emotions and limited subtopics from emotion research while neglecting an overall and holistic perspective that would help to develop common ground in this area. For instance, concerning KM processes, the roles of emotional intelligence (Decker et al., 2009; Peng, 2013; Trong Tuan, 2013) and emotional obstacles (Lin et al., 2006; Pemberton et al., 2007) have been investigated. However, an integrated and comprehensive overview of emotions, unbiased by any particular single topic, is still lacking, and it is necessary to consolidate research on single emotions and emotional concepts (Hornung & Smolnik, 2018), and in which nexus they are displayed in KM research – with a taxonomy of emotions in KM research as the ultimate goal. To arrive at a comprehensive taxonomy of emotions in KM and close the aforementioned gap, it is crucial to understand which emotions are prevalent in and dominate KM research. Sentiment analyses, which have often been used to detect words associated with either positive or negative emotions in the context of politics, finance, and (social media) marketing (Matthies, 2016; Yassine & Hajj, 2010), are a useful instrument to gain a broader understanding of emotions. As a special type of text mining, sentiment analyses support the authors’ goal of analyzing the underlying sentiment of a text that “can encompass investigating both the opinion and the emotion behind that unit” (Yadollahi et al., 2017, p. 2). Sentiment analyses also enable the exploration of vast amounts of data. They are also effective at revealing which emotions prevail in written KM publications and can, therefore, help to answer the following research questions:
RQ1: Which emotions dominate research on KM?
RQ2: How can these emotions be categorized according to emotion scales?
The sentiment analysis in this study relies on a dictionary-based approach in which KM-specific dictionaries 1) are created based on Hu and Liu (2004) and 2) applied to a comprehensive sample of 6,017 scientific KM publications to detect existing emotions. The analysis results are then 3) categorized and structured using an appropriate emotion scale.

the corresponding author is Olivia Hornung, the lead author is Nora Fteimi and the 3rd author is Stefan Smolnik, they are from the universities of Hagen and Passau in Germany.  Stefan is a research partner of mine but this research comes from his research team at Hagen.....murray


-----Original Message-----
From: Matt Moore <matt@...>
To: main@sikm.groups.io
Sent: Fri, Sep 25, 2020 9:24 pm
Subject: Re: [SIKM] Emotions & KM

What is it about and who is it by?

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 1:28 PM, Murray Jennex via groups.io <murphjen@...> wrote:


my journal has another KM and emotions article coming out in 2021


Dennis Thomas
 

Hello Matt,

I have some thoughts related to your “emotion” presentation.  Since I consider things from a technology point-of-view, I look at the human component differently than most other people. 

(1)   I make a distinction between cognitive, emotion, and behavior

(2) In general, I see the cognitive component as rational and logical reasoning.  Most technologists conflate rational reasoning with logical reasoning.  So, if a person is not thinking logically, then they are by default reacting emotionally. I distinguish the two modes of reasoning as follows (my descriptions):

Rational Reasoning – Innate human reasoning.  Purposeful, imaginative, goal-oriented reasoning processes that solve problems or predicts impacts, outcomes, and consequences.  Rational thought considers every possible variable (dependencies, contingencies, cross-references, causal relationships, etc.), and points-of-view that argue for or against something.  Rational thought solves problems, is used for planning and general human-to-human interactions.  It gives the facts associated with situations and circumstances their context, meaning, and purpose.  

Logical Reasoning – Man-made, rule-based reasoning systems requiring binary true/false, yes/no verification.  Logic requires self-consistency and looks for self-consistent answers.  Linguistics and general mathematics are based on rules and axiomatic assertions.   Most programming languages are based on logic as demonstrated by algorithms which are designed to execute self-consistent, repetitious, functions and tasks. 

(3) Emotion is reactionary from my point of view.  If you walk into your local coffee shop and see a friend, you are naturally inclination is to walk over to them to say hello.  What if they did not respond to your greeting?  What if they just sat in their chair looking up at you and not responding as if they knew you at all?  Your emotional reaction would be what is going on here?  Which would turn, perhaps, to concern?  Or, eventually, to frustration or anger.  

We have all experienced an emotional reaction to logic-based technologies that have stripped away any humanity because they are rule based and are only designed to respond to how their code instructs them to respond.  AI, ML, NLP do not understand the meaning of words, their context, meaning, or purpose.  Human rationality does.  People commonly experience a wide range of emotions when working with technology because it does not work the way people naturally think. Before any manmade artifact came into being, it had to go through the rational reasoning process. 

(4) Behavior, from our point-of-view, has deep roots in our need to survive, to belong, to meet and exceed expectations for our own personal self-esteem.   Organizations that are staffed with ambitious people with “getting better agendas” are sustained because those organizations naturally weed out those individuals who cannot rise to the level of excellence that the organization and their peers aspire to, or have achieved.  This has been validated antidotally, through surveys, and research. 

For whatever it is worth --

Dennis L. Thomas
IQStrategix
(810) 662-5199

Leveraging Organizational Knowledge 



On September 25, 2020 at 7:34:04 PM, Matt Moore (matt@...) wrote:

Hi,

So as you will have seen from Stan's email, I will be doing a session
on emotions and KM in later October.

I have started work on the presentation but I'd be interested to hear
thoughts from the community on this topic.

- How do KM and emotion inter-relate?
- What role do emotions (of ourselves, of others) play in the work that we do?
- How are different emotions bound up with knowledge and how do the
impact knowledge creation, knowledge dissemination, and knowledge use?

BTW emotions are a big part of being human but a literature search
reveals only about 10-20 articles on emotion and KM over the last 20
years.

Regards,
--
Matt Moore
M. +61 (0) 423 784 504
matt@...






Nancy Dixon
 

Although narrower than the whole field of KM, there are studies of emotion related to knowledge transfer: from Szulanski and Lee 2020 paper in the Oxford Handbook on Organizational learning 

" The transfer’s success depends to a certain extent on the quality of the relationship between source and recipient, detectable in the ease of communication (Arrow, 1974) and in the “intimacy” of their relationship (Marsden, 1990). It has been suggested by scholars that an arduous relationship between the knowledge source and recipient has the potential to increase dramatically the difficulty of a particular transfer ( Szulanski , 1996; Szulanski et al., 2016). 


Nancy

On Sep 26, 2020, at 12:33 AM, Matt Moore via groups.io <matt@...> wrote:

Thanks Murray,

I have read the conference paper I think this research is based on - and a previous paper by Hornung & Smolnik. I’ll be incorporating some of both of them into my presso.

I think the earlier paper is a good literature review. My main issue with their approach is that they seem to be conducting purely secondary research - trying to mine the academic literature in ever more elaborate ways. I would like to see 1. more primary investigation and 2. more “so what”.

BTW one of the issues with the research on emotion in general (not just KM) is the dissonance between content & form. The writing is as bloodless as the topics are intense.

Regards,

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 2:36 PM, Murray Jennex via groups.io <murphjen@...> wrote:


When Emotions Rule Knowledge: A Text-Mining Study of Emotions in Knowledge Management Research

Emotions are as much a part of human behavior as reason and play an important role in intelligence and knowledge (Martı́nez-Miranda & Aldea, 2005). Managing knowledge in organizations has proved to be very useful since successful knowledge management (KM) leads to significant improvements in their scientific, economic, and social aspects (Cao et al., 2012). Nonetheless, knowledge is often viewed merely as just another manageable organizational resource (Alavi & Leidner, 2001). Owing to its context-specificity and boundedness to human beings (Nonaka, 1994), however, it cannot be separated from human emotions and, thus, has to be approached differently than other organizational resources (Kuo et al., 2003). Consequently, the role played by emotions, which help to both express and understand knowledge (Davenport & Prusak, 1998), requires attention from within the information systems (IS) domain in general and from KM researchers in particular.
 
IS researchers have started to pay attention to the presence and role of emotions (Chau et al., 2020; Beaudry & Pinsonneault, 2010; Gregor et al., 2014). Likewise, KM studies on emotion-related topics are critical to acknowledging emotions and the role emotional concepts play in KM (Scherer & Tran, 2003; van den Hooff et al., 2012). Nonetheless, these studies also show how compartmentalized KM research on emotions is. It only focuses on single emotions and limited subtopics from emotion research while neglecting an overall and holistic perspective that would help to develop common ground in this area. For instance, concerning KM processes, the roles of emotional intelligence (Decker et al., 2009; Peng, 2013; Trong Tuan, 2013) and emotional obstacles (Lin et al., 2006; Pemberton et al., 2007) have been investigated. However, an integrated and comprehensive overview of emotions, unbiased by any particular single topic, is still lacking, and it is necessary to consolidate research on single emotions and emotional concepts (Hornung & Smolnik, 2018), and in which nexus they are displayed in KM research – with a taxonomy of emotions in KM research as the ultimate goal. To arrive at a comprehensive taxonomy of emotions in KM and close the aforementioned gap, it is crucial to understand which emotions are prevalent in and dominate KM research. Sentiment analyses, which have often been used to detect words associated with either positive or negative emotions in the context of politics, finance, and (social media) marketing (Matthies, 2016; Yassine & Hajj, 2010), are a useful instrument to gain a broader understanding of emotions. As a special type of text mining, sentiment analyses support the authors’ goal of analyzing the underlying sentiment of a text that “can encompass investigating both the opinion and the emotion behind that unit” (Yadollahi et al., 2017, p. 2). Sentiment analyses also enable the exploration of vast amounts of data. They are also effective at revealing which emotions prevail in written KM publications and can, therefore, help to answer the following research questions:
RQ1: Which emotions dominate research on KM?
RQ2: How can these emotions be categorized according to emotion scales?
The sentiment analysis in this study relies on a dictionary-based approach in which KM-specific dictionaries 1) are created based on Hu and Liu (2004) and 2) applied to a comprehensive sample of 6,017 scientific KM publications to detect existing emotions. The analysis results are then 3) categorized and structured using an appropriate emotion scale.

the corresponding author is Olivia Hornung, the lead author is Nora Fteimi and the 3rd author is Stefan Smolnik, they are from the universities of Hagen and Passau in Germany.  Stefan is a research partner of mine but this research comes from his research team at Hagen.....murray


-----Original Message-----
From: Matt Moore <matt@...>
To: main@sikm.groups.io
Sent: Fri, Sep 25, 2020 9:24 pm
Subject: Re: [SIKM] Emotions & KM

What is it about and who is it by?

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 1:28 PM, Murray Jennex via groups.io <murphjen@...> wrote:


my journal has another KM and emotions article coming out in 2021


Matt Moore
 

Hi Dennis,

Thanks for your reply. A few points in response.

1. Your distinction between cognition, emotion & behaviour sounds a lot like the ABC (affect, behaviour, cognition) model of attitudes. My reading of this model is that the three components are useful lenses through which to understand attitudes - but that they are not independent of each other. Our attitudes don't divide up neatly into these three bits.

2. “Rational thought considers every possible variable“

Naturalistic Decision Making (NDM) researchers would say that isn’t true. The vast majority of human decision making does not involve the consideration of every variable. People pattern match. Now you might say “that means people are mostly irrational”. To which an NDMer might reply: “So what? It’s an approach that mostly works for people and we’re interested in how people actually make decisions rather than how you think they should make decisions.”

3. I wouldn't split off cognition from emotion. And I wouldn't see cognition as being primarily about reason and logic. A lot of the research from the last 30 years has investigated how emotion and reason are intertwined. Our thoughts and feelings are not separate. 

4. In terms of how people interact with machines and their emotional responses to them, I do actually want to tackle this in the talk. I'm probably going to be leaning heavily on Don Norman's Emotional Design here: https://www.nngroup.com/books/emotional-design/

Regards,

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 9:23 PM, Dennis Thomas <dlthomas@...> wrote:


Hello Matt,

I have some thoughts related to your “emotion” presentation.  Since I consider things from a technology point-of-view, I look at the human component differently than most other people. 

(1)   I make a distinction between cognitive, emotion, and behavior

(2) In general, I see the cognitive component as rational and logical reasoning.  Most technologists conflate rational reasoning with logical reasoning.  So, if a person is not thinking logically, then they are by default reacting emotionally. I distinguish the two modes of reasoning as follows (my descriptions):

Rational Reasoning – Innate human reasoning.  Purposeful, imaginative, goal-oriented reasoning processes that solve problems or predicts impacts, outcomes, and consequences.  Rational thought considers every possible variable (dependencies, contingencies, cross-references, causal relationships, etc.), and points-of-view that argue for or against.  Rational thought solves problems, is used for planning and general human-to-human interactions.  It gives the facts associated with situations and circumstances their context, meaning, and purpose.  

Logical Reasoning – Man-made, rule-based reasoning systems requiring binary true/false, yes/no verification.  Logic requires self-consistency and looks for self-consistent answers.  Linguistics and general mathematics are based on rules and axiomatic assertions.   Most programming languages are based on logic as demonstrated by algorithms which are designed to execute self-consistent, repetitious, functions and tasks. 

(3) Emotion is reactionary from my point of view.  If you walk into your local coffee shop and see a friend, you are naturally inclination is to walk over to them to say hello.  What if they did not respond to your greeting?  What if they just sat in their chair looking up at you and not responding as if they knew you at all?  Your emotional reaction would be what is going on here?  Which would turn, perhaps, to concern?  Or, eventually, to frustration or anger.  

We have all experienced an emotional reaction to logic-based technologies that have stripped away any humanity because they are rule based and are only designed to respond to how their code instructs them to respond.  AI, ML, NLP do not understand the meaning of words, their context, meaning, or purpose.  Human rationality does.  People commonly experience a wide range of emotions when working with technology because it does not work the way people naturally think. Before any manmade artifact came into being, it had to go through the rational reasoning process. 

(4) Behavior, from our point-of-view, has deep roots in our need to survive, to belong, to meet and exceed expectations for our own personal self-esteem.   Organizations that are staffed with ambitious people with “getting better agendas” are sustained because those organizations naturally weed out those individuals who cannot rise to the level of excellence that the organization and their peers aspire to, or have achieved.  This has been validated antidotally, through surveys, and research. 

For whatever it is worth --

Dennis L. Thomas
IQStrategix
(810) 662-5199

Leveraging Organizational Knowledge 



On September 25, 2020 at 7:34:04 PM, Matt Moore (matt@...) wrote:

Hi,

So as you will have seen from Stan's email, I will be doing a session
on emotions and KM in later October.

I have started work on the presentation but I'd be interested to hear
thoughts from the community on this topic.

- How do KM and emotion inter-relate?
- What role do emotions (of ourselves, of others) play in the work that we do?
- How are different emotions bound up with knowledge and how do the
impact knowledge creation, knowledge dissemination, and knowledge use?

BTW emotions are a big part of being human but a literature search
reveals only about 10-20 articles on emotion and KM over the last 20
years.

Regards,
--
Matt Moore
M. +61 (0) 423 784 504
matt@...






Matt Moore
 

Thanks for the references Patrick,

I couldn't access the Mandler one but the Company Command one had this nugget in it: "For many leaders, this is the first time they had experienced these extreme emotions. As a consequence, they learned how to manage these intense emotions, both in themselves and in others. Based on this observation, we argue that any course in crisis leadership should explicitly address the intense emotional component of crisis leadership".

Last year, I was involved in a program to develop innovative ways of teaching ethics to kids. One common technique is scenarios. However one weakness with scenarios (e.g. the now-infamous trolley problem) is that deciding these things hypothetically and in a safe environment is very different to deciding in a real world situation where people may live or die.

BTW I also found this paper on emotion and organizational learning interesting - plus it has a great title: https://www.academia.edu/32900520/Uncomfortable_KnowledgeManagement_The_Impact_of_Emotion_on_Organisational_Learning

Also: I am trying to avoid using the term "affect" as most non-specialists don't know what it means

Regards,

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 3:07 PM, Patrick Lambe <plambe@...> wrote:

Matt - there’s more on emotions in the context of learning - “affect” is the term typically used.

Nate Allen (of Company Command fame) did a study with colleagues on the role of emotional affect in learning and leadership in crisis situations. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.845.7532&rep=rep1&type=pdf

George Mandler did a study on affect, problem solving and memory in the 1980s. The link is to an e-book on affect and mathematical problem solving (educational focus), Mandler's paper is chapter 1 https://d1wqtxts1xzle7.cloudfront.net/63633380/affect_and_mathematical_problem_solving20200615-98668-qo4e09.pdf

P



Patrick Lambe
Partner
Straits Knowledge

phone:  +65 98528511

web:  www.straitsknowledge.com
resources:  www.greenchameleon.com
knowledge mapping:  www.aithinsoftware.com



Stephen Bounds
 

Hi Matt,

Notwithstanding your commendable attempt to steer clear of jargon, I do note that there's a pretty strong case for considering affect universal and emotion subjective. Dr Barrett has been looking into this for a long time, and her view of the difference is summarised nicely by a reviewer of a recent book:

Emotions are neither universal nor located in specific brain regions; they vary by culture and result from dynamic neuronal networks. These networks run nonstop simulations, making predictions and correcting them based on the environment rather than reacting to it.

More technically, Dr Barrett notes:

Numerous studies find evidence for valence and arousal [ie affect] around the world. When people view abstract visual patterns and describe their aesthetic reactions, they appear to do so universally with valence and arousal. Participants from India (Gujarati), Spain, Vietnam, Hong Kong, Haiti, Greece, China, Croatia, Estonia, Japan, and Poland were asked to judge the similarities and differences between pairs of emotion words. When scientists used statistics (multidimensional scaling) to extract the dimensions of similarity by statistical means, they found both valence and arousal. Valence and arousal also describe the properties of people’s affective feelings in the U.S., Canada, Spain, China, Japan, and Korea. When people from Greece, China, the Netherlands, and of course the US judged the similarity and differences of stereotyped emotion poses of the basic emotion method, similar valence and arousal dimensions were observed to underlie these judgments.

Cheers,
Stephen.
====================================
Stephen Bounds
Executive, Information Management
Cordelta
E: stephen.bounds@...
M: 0401 829 096
====================================
On 27/09/2020 9:04 am, Matt Moore wrote:
Thanks for the references Patrick,

I couldn't access the Mandler one but the Company Command one had this nugget in it: "For many leaders, this is the first time they had experienced these extreme emotions. As a consequence, they learned how to manage these intense emotions, both in themselves and in others. Based on this observation, we argue that any course in crisis leadership should explicitly address the intense emotional component of crisis leadership".

Last year, I was involved in a program to develop innovative ways of teaching ethics to kids. One common technique is scenarios. However one weakness with scenarios (e.g. the now-infamous trolley problem) is that deciding these things hypothetically and in a safe environment is very different to deciding in a real world situation where people may live or die.

BTW I also found this paper on emotion and organizational learning interesting - plus it has a great title: https://www.academia.edu/32900520/Uncomfortable_KnowledgeManagement_The_Impact_of_Emotion_on_Organisational_Learning

Also: I am trying to avoid using the term "affect" as most non-specialists don't know what it means

Regards,

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 3:07 PM, Patrick Lambe <plambe@...> wrote:

Matt - there’s more on emotions in the context of learning - “affect” is the term typically used.

Nate Allen (of Company Command fame) did a study with colleagues on the role of emotional affect in learning and leadership in crisis situations. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.845.7532&rep=rep1&type=pdf

George Mandler did a study on affect, problem solving and memory in the 1980s. The link is to an e-book on affect and mathematical problem solving (educational focus), Mandler's paper is chapter 1 https://d1wqtxts1xzle7.cloudfront.net/63633380/affect_and_mathematical_problem_solving20200615-98668-qo4e09.pdf

P



Patrick Lambe
Partner
Straits Knowledge

phone:  +65 98528511

web:  www.straitsknowledge.com
resources:  www.greenchameleon.com
knowledge mapping:  www.aithinsoftware.com



Matt Moore
 

Hi Stephen,

Thanks for the reference.

“Emotions are neither universal nor located in specific brain regions” - that makes sense to me.

“affect universal and emotion subjective”

Again, this also makes sense. Given human physiology, it would be surprising if elements of emotion weren’t universal. And given that emotion is tied up with our life experience and worldview, it would be surprising if elements of emotion weren’t culturally specific.

So the question is: what does this mean for knowledge managers? Is it simply another aspect of the need for cross-cultural awareness?

Regards,

Matt Moore
+61 423 784 504

On Sep 27, 2020, at 10:11 AM, Stephen Bounds <km@...> wrote:



Hi Matt,

Notwithstanding your commendable attempt to steer clear of jargon, I do note that there's a pretty strong case for considering affect universal and emotion subjective. Dr Barrett has been looking into this for a long time, and her view of the difference is summarised nicely by a reviewer of a recent book:

Emotions are neither universal nor located in specific brain regions; they vary by culture and result from dynamic neuronal networks. These networks run nonstop simulations, making predictions and correcting them based on the environment rather than reacting to it.

More technically, Dr Barrett notes:

Numerous studies find evidence for valence and arousal [ie affect] around the world. When people view abstract visual patterns and describe their aesthetic reactions, they appear to do so universally with valence and arousal. Participants from India (Gujarati), Spain, Vietnam, Hong Kong, Haiti, Greece, China, Croatia, Estonia, Japan, and Poland were asked to judge the similarities and differences between pairs of emotion words. When scientists used statistics (multidimensional scaling) to extract the dimensions of similarity by statistical means, they found both valence and arousal. Valence and arousal also describe the properties of people’s affective feelings in the U.S., Canada, Spain, China, Japan, and Korea. When people from Greece, China, the Netherlands, and of course the US judged the similarity and differences of stereotyped emotion poses of the basic emotion method, similar valence and arousal dimensions were observed to underlie these judgments.

Cheers,
Stephen.
====================================
Stephen Bounds
Executive, Information Management
Cordelta
E: stephen.bounds@...
M: 0401 829 096
====================================
On 27/09/2020 9:04 am, Matt Moore wrote:
Thanks for the references Patrick,

I couldn't access the Mandler one but the Company Command one had this nugget in it: "For many leaders, this is the first time they had experienced these extreme emotions. As a consequence, they learned how to manage these intense emotions, both in themselves and in others. Based on this observation, we argue that any course in crisis leadership should explicitly address the intense emotional component of crisis leadership".

Last year, I was involved in a program to develop innovative ways of teaching ethics to kids. One common technique is scenarios. However one weakness with scenarios (e.g. the now-infamous trolley problem) is that deciding these things hypothetically and in a safe environment is very different to deciding in a real world situation where people may live or die.

BTW I also found this paper on emotion and organizational learning interesting - plus it has a great title: https://www.academia.edu/32900520/Uncomfortable_KnowledgeManagement_The_Impact_of_Emotion_on_Organisational_Learning

Also: I am trying to avoid using the term "affect" as most non-specialists don't know what it means

Regards,

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 3:07 PM, Patrick Lambe <plambe@...> wrote:

Matt - there’s more on emotions in the context of learning - “affect” is the term typically used.

Nate Allen (of Company Command fame) did a study with colleagues on the role of emotional affect in learning and leadership in crisis situations. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.845.7532&rep=rep1&type=pdf

George Mandler did a study on affect, problem solving and memory in the 1980s. The link is to an e-book on affect and mathematical problem solving (educational focus), Mandler's paper is chapter 1 https://d1wqtxts1xzle7.cloudfront.net/63633380/affect_and_mathematical_problem_solving20200615-98668-qo4e09.pdf

P



Patrick Lambe
Partner
Straits Knowledge

phone:  +65 98528511

web:  www.straitsknowledge.com
resources:  www.greenchameleon.com
knowledge mapping:  www.aithinsoftware.com



Matt Moore
 

Thanks Nancy!

I have noticed that a fair few of the research papers on emotion & KM seem to be specifically about emotional intelligence & knowledge transfer.

How would you see this playing out in practice for knowledge managers?

Regards,

Matt Moore
+61 423 784 504

On Sep 27, 2020, at 3:12 AM, Nancy Dixon <nancydixon@...> wrote:

 Although narrower than the whole field of KM, there are studies of emotion related to knowledge transfer: from Szulanski and Lee 2020 paper in the Oxford Handbook on Organizational learning 

" The transfer’s success depends to a certain extent on the quality of the relationship between source and recipient, detectable in the ease of communication (Arrow, 1974) and in the “intimacy” of their relationship (Marsden, 1990). It has been suggested by scholars that an arduous relationship between the knowledge source and recipient has the potential to increase dramatically the difficulty of a particular transfer ( Szulanski , 1996; Szulanski et al., 2016). 


Nancy

On Sep 26, 2020, at 12:33 AM, Matt Moore via groups.io <matt@...> wrote:

Thanks Murray,

I have read the conference paper I think this research is based on - and a previous paper by Hornung & Smolnik. I’ll be incorporating some of both of them into my presso.

I think the earlier paper is a good literature review. My main issue with their approach is that they seem to be conducting purely secondary research - trying to mine the academic literature in ever more elaborate ways. I would like to see 1. more primary investigation and 2. more “so what”.

BTW one of the issues with the research on emotion in general (not just KM) is the dissonance between content & form. The writing is as bloodless as the topics are intense.

Regards,

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 2:36 PM, Murray Jennex via groups.io <murphjen@...> wrote:


When Emotions Rule Knowledge: A Text-Mining Study of Emotions in Knowledge Management Research

Emotions are as much a part of human behavior as reason and play an important role in intelligence and knowledge (Martı́nez-Miranda & Aldea, 2005). Managing knowledge in organizations has proved to be very useful since successful knowledge management (KM) leads to significant improvements in their scientific, economic, and social aspects (Cao et al., 2012). Nonetheless, knowledge is often viewed merely as just another manageable organizational resource (Alavi & Leidner, 2001). Owing to its context-specificity and boundedness to human beings (Nonaka, 1994), however, it cannot be separated from human emotions and, thus, has to be approached differently than other organizational resources (Kuo et al., 2003). Consequently, the role played by emotions, which help to both express and understand knowledge (Davenport & Prusak, 1998), requires attention from within the information systems (IS) domain in general and from KM researchers in particular.
 
IS researchers have started to pay attention to the presence and role of emotions (Chau et al., 2020; Beaudry & Pinsonneault, 2010; Gregor et al., 2014). Likewise, KM studies on emotion-related topics are critical to acknowledging emotions and the role emotional concepts play in KM (Scherer & Tran, 2003; van den Hooff et al., 2012). Nonetheless, these studies also show how compartmentalized KM research on emotions is. It only focuses on single emotions and limited subtopics from emotion research while neglecting an overall and holistic perspective that would help to develop common ground in this area. For instance, concerning KM processes, the roles of emotional intelligence (Decker et al., 2009; Peng, 2013; Trong Tuan, 2013) and emotional obstacles (Lin et al., 2006; Pemberton et al., 2007) have been investigated. However, an integrated and comprehensive overview of emotions, unbiased by any particular single topic, is still lacking, and it is necessary to consolidate research on single emotions and emotional concepts (Hornung & Smolnik, 2018), and in which nexus they are displayed in KM research – with a taxonomy of emotions in KM research as the ultimate goal. To arrive at a comprehensive taxonomy of emotions in KM and close the aforementioned gap, it is crucial to understand which emotions are prevalent in and dominate KM research. Sentiment analyses, which have often been used to detect words associated with either positive or negative emotions in the context of politics, finance, and (social media) marketing (Matthies, 2016; Yassine & Hajj, 2010), are a useful instrument to gain a broader understanding of emotions. As a special type of text mining, sentiment analyses support the authors’ goal of analyzing the underlying sentiment of a text that “can encompass investigating both the opinion and the emotion behind that unit” (Yadollahi et al., 2017, p. 2). Sentiment analyses also enable the exploration of vast amounts of data. They are also effective at revealing which emotions prevail in written KM publications and can, therefore, help to answer the following research questions:
RQ1: Which emotions dominate research on KM?
RQ2: How can these emotions be categorized according to emotion scales?
The sentiment analysis in this study relies on a dictionary-based approach in which KM-specific dictionaries 1) are created based on Hu and Liu (2004) and 2) applied to a comprehensive sample of 6,017 scientific KM publications to detect existing emotions. The analysis results are then 3) categorized and structured using an appropriate emotion scale.

the corresponding author is Olivia Hornung, the lead author is Nora Fteimi and the 3rd author is Stefan Smolnik, they are from the universities of Hagen and Passau in Germany.  Stefan is a research partner of mine but this research comes from his research team at Hagen.....murray


-----Original Message-----
From: Matt Moore <matt@...>
To: main@sikm.groups.io
Sent: Fri, Sep 25, 2020 9:24 pm
Subject: Re: [SIKM] Emotions & KM

What is it about and who is it by?

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 1:28 PM, Murray Jennex via groups.io <murphjen@...> wrote:


my journal has another KM and emotions article coming out in 2021


Aprill Allen
 

One of the most significant emotions we deal with in the KM domain is fear. 

The most primal is fear of being made redundant by giving away knowledge. 

Fear of not being promoted or recognised because someone else will get the credit. 

Fear of being wrong or inadequate by sharing something less than “perfect”. 

Fear of being reprimanded because knowledge capture takes time and impacts my KPIs. 

Fear of loss of prestige, status or bonuses because the compensation structure is aligned with competition rather than collaboration. 

Knowledge managers have to overcome all these by working with leadership (ideally) to communicate the benefits to individuals and teams, to reconnect with common big picture goals and vision, and to rally around a coordinated effort. When belonging and excitement overtake fear, that’s when the big payoffs materialise. 

On Sun, 27 Sep 2020 at 10:32 am, Matt Moore <matt@...> wrote:
Thanks Nancy!

I have noticed that a fair few of the research papers on emotion & KM seem to be specifically about emotional intelligence & knowledge transfer.

How would you see this playing out in practice for knowledge managers?

Regards,

Matt Moore
+61 423 784 504

On Sep 27, 2020, at 3:12 AM, Nancy Dixon <nancydixon@...> wrote:

 Although narrower than the whole field of KM, there are studies of emotion related to knowledge transfer: from Szulanski and Lee 2020 paper in the Oxford Handbook on Organizational learning 

" The transfer’s success depends to a certain extent on the quality of the relationship between source and recipient, detectable in the ease of communication (Arrow, 1974) and in the “intimacy” of their relationship (Marsden, 1990). It has been suggested by scholars that an arduous relationship between the knowledge source and recipient has the potential to increase dramatically the difficulty of a particular transfer ( Szulanski , 1996; Szulanski et al., 2016). 


Nancy

On Sep 26, 2020, at 12:33 AM, Matt Moore via groups.io <matt@...> wrote:

Thanks Murray,

I have read the conference paper I think this research is based on - and a previous paper by Hornung & Smolnik. I’ll be incorporating some of both of them into my presso.

I think the earlier paper is a good literature review. My main issue with their approach is that they seem to be conducting purely secondary research - trying to mine the academic literature in ever more elaborate ways. I would like to see 1. more primary investigation and 2. more “so what”.

BTW one of the issues with the research on emotion in general (not just KM) is the dissonance between content & form. The writing is as bloodless as the topics are intense.

Regards,

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 2:36 PM, Murray Jennex via groups.io <murphjen@...> wrote:


When Emotions Rule Knowledge: A Text-Mining Study of Emotions in Knowledge Management Research

Emotions are as much a part of human behavior as reason and play an important role in intelligence and knowledge (Martı́nez-Miranda & Aldea, 2005). Managing knowledge in organizations has proved to be very useful since successful knowledge management (KM) leads to significant improvements in their scientific, economic, and social aspects (Cao et al., 2012). Nonetheless, knowledge is often viewed merely as just another manageable organizational resource (Alavi & Leidner, 2001). Owing to its context-specificity and boundedness to human beings (Nonaka, 1994), however, it cannot be separated from human emotions and, thus, has to be approached differently than other organizational resources (Kuo et al., 2003). Consequently, the role played by emotions, which help to both express and understand knowledge (Davenport & Prusak, 1998), requires attention from within the information systems (IS) domain in general and from KM researchers in particular.
 
IS researchers have started to pay attention to the presence and role of emotions (Chau et al., 2020; Beaudry & Pinsonneault, 2010; Gregor et al., 2014). Likewise, KM studies on emotion-related topics are critical to acknowledging emotions and the role emotional concepts play in KM (Scherer & Tran, 2003; van den Hooff et al., 2012). Nonetheless, these studies also show how compartmentalized KM research on emotions is. It only focuses on single emotions and limited subtopics from emotion research while neglecting an overall and holistic perspective that would help to develop common ground in this area. For instance, concerning KM processes, the roles of emotional intelligence (Decker et al., 2009; Peng, 2013; Trong Tuan, 2013) and emotional obstacles (Lin et al., 2006; Pemberton et al., 2007) have been investigated. However, an integrated and comprehensive overview of emotions, unbiased by any particular single topic, is still lacking, and it is necessary to consolidate research on single emotions and emotional concepts (Hornung & Smolnik, 2018), and in which nexus they are displayed in KM research – with a taxonomy of emotions in KM research as the ultimate goal. To arrive at a comprehensive taxonomy of emotions in KM and close the aforementioned gap, it is crucial to understand which emotions are prevalent in and dominate KM research. Sentiment analyses, which have often been used to detect words associated with either positive or negative emotions in the context of politics, finance, and (social media) marketing (Matthies, 2016; Yassine & Hajj, 2010), are a useful instrument to gain a broader understanding of emotions. As a special type of text mining, sentiment analyses support the authors’ goal of analyzing the underlying sentiment of a text that “can encompass investigating both the opinion and the emotion behind that unit” (Yadollahi et al., 2017, p. 2). Sentiment analyses also enable the exploration of vast amounts of data. They are also effective at revealing which emotions prevail in written KM publications and can, therefore, help to answer the following research questions:
RQ1: Which emotions dominate research on KM?
RQ2: How can these emotions be categorized according to emotion scales?
The sentiment analysis in this study relies on a dictionary-based approach in which KM-specific dictionaries 1) are created based on Hu and Liu (2004) and 2) applied to a comprehensive sample of 6,017 scientific KM publications to detect existing emotions. The analysis results are then 3) categorized and structured using an appropriate emotion scale.

the corresponding author is Olivia Hornung, the lead author is Nora Fteimi and the 3rd author is Stefan Smolnik, they are from the universities of Hagen and Passau in Germany.  Stefan is a research partner of mine but this research comes from his research team at Hagen.....murray


-----Original Message-----
From: Matt Moore <matt@...>
To: main@sikm.groups.io
Sent: Fri, Sep 25, 2020 9:24 pm
Subject: Re: [SIKM] Emotions & KM

What is it about and who is it by?

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 1:28 PM, Murray Jennex via groups.io <murphjen@...> wrote:


my journal has another KM and emotions article coming out in 2021

--
--

Aprill Allen
Founder and Managing Director | Knowledge Bird
Knowledge management consulting & KCS Trainer
M: +61 400 101 961
knowledgebird.com


Nancy Dixon
 

Matt,
One simple practice is that if two teams have an “arduous’ relationship, rather than bringing them together initially you start with and exchange of written documents. After these have been reviewed, the group could move toward coming together for the receiver to gain knowledge from the source. However, you would want to spend the initial time together for them to build a relationship, have dinner together, talking about projects they worked on, sports teams etc. I call that “connection before content.” When they are in relationship with each other, then it is possible for the recipient to be open to learn from the source.  

Nancy

On Sep 26, 2020, at 7:31 PM, Matt Moore via groups.io <matt@...> wrote:

Thanks Nancy!

I have noticed that a fair few of the research papers on emotion & KM seem to be specifically about emotional intelligence & knowledge transfer.

How would you see this playing out in practice for knowledge managers?

Regards,

Matt Moore
+61 423 784 504

On Sep 27, 2020, at 3:12 AM, Nancy Dixon <nancydixon@...> wrote:

 Although narrower than the whole field of KM, there are studies of emotion related to knowledge transfer: from Szulanski and Lee 2020 paper in the Oxford Handbook on Organizational learning 

" The transfer’s success depends to a certain extent on the quality of the relationship between source and recipient, detectable in the ease of communication (Arrow, 1974) and in the “intimacy” of their relationship (Marsden, 1990). It has been suggested by scholars that an arduous relationship between the knowledge source and recipient has the potential to increase dramatically the difficulty of a particular transfer ( Szulanski , 1996; Szulanski et al., 2016). 


Nancy

On Sep 26, 2020, at 12:33 AM, Matt Moore via groups.io <matt@...> wrote:

Thanks Murray,

I have read the conference paper I think this research is based on - and a previous paper by Hornung & Smolnik. I’ll be incorporating some of both of them into my presso.

I think the earlier paper is a good literature review. My main issue with their approach is that they seem to be conducting purely secondary research - trying to mine the academic literature in ever more elaborate ways. I would like to see 1. more primary investigation and 2. more “so what”.

BTW one of the issues with the research on emotion in general (not just KM) is the dissonance between content & form. The writing is as bloodless as the topics are intense.

Regards,

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 2:36 PM, Murray Jennex via groups.io <murphjen@...> wrote:


When Emotions Rule Knowledge: A Text-Mining Study of Emotions in Knowledge Management Research

Emotions are as much a part of human behavior as reason and play an important role in intelligence and knowledge (Martı́nez-Miranda & Aldea, 2005). Managing knowledge in organizations has proved to be very useful since successful knowledge management (KM) leads to significant improvements in their scientific, economic, and social aspects (Cao et al., 2012). Nonetheless, knowledge is often viewed merely as just another manageable organizational resource (Alavi & Leidner, 2001). Owing to its context-specificity and boundedness to human beings (Nonaka, 1994), however, it cannot be separated from human emotions and, thus, has to be approached differently than other organizational resources (Kuo et al., 2003). Consequently, the role played by emotions, which help to both express and understand knowledge (Davenport & Prusak, 1998), requires attention from within the information systems (IS) domain in general and from KM researchers in particular.
 
IS researchers have started to pay attention to the presence and role of emotions (Chau et al., 2020; Beaudry & Pinsonneault, 2010; Gregor et al., 2014). Likewise, KM studies on emotion-related topics are critical to acknowledging emotions and the role emotional concepts play in KM (Scherer & Tran, 2003; van den Hooff et al., 2012). Nonetheless, these studies also show how compartmentalized KM research on emotions is. It only focuses on single emotions and limited subtopics from emotion research while neglecting an overall and holistic perspective that would help to develop common ground in this area. For instance, concerning KM processes, the roles of emotional intelligence (Decker et al., 2009; Peng, 2013; Trong Tuan, 2013) and emotional obstacles (Lin et al., 2006; Pemberton et al., 2007) have been investigated. However, an integrated and comprehensive overview of emotions, unbiased by any particular single topic, is still lacking, and it is necessary to consolidate research on single emotions and emotional concepts (Hornung & Smolnik, 2018), and in which nexus they are displayed in KM research – with a taxonomy of emotions in KM research as the ultimate goal. To arrive at a comprehensive taxonomy of emotions in KM and close the aforementioned gap, it is crucial to understand which emotions are prevalent in and dominate KM research. Sentiment analyses, which have often been used to detect words associated with either positive or negative emotions in the context of politics, finance, and (social media) marketing (Matthies, 2016; Yassine & Hajj, 2010), are a useful instrument to gain a broader understanding of emotions. As a special type of text mining, sentiment analyses support the authors’ goal of analyzing the underlying sentiment of a text that “can encompass investigating both the opinion and the emotion behind that unit” (Yadollahi et al., 2017, p. 2). Sentiment analyses also enable the exploration of vast amounts of data. They are also effective at revealing which emotions prevail in written KM publications and can, therefore, help to answer the following research questions:
RQ1: Which emotions dominate research on KM?
RQ2: How can these emotions be categorized according to emotion scales?
The sentiment analysis in this study relies on a dictionary-based approach in which KM-specific dictionaries 1) are created based on Hu and Liu (2004) and 2) applied to a comprehensive sample of 6,017 scientific KM publications to detect existing emotions. The analysis results are then 3) categorized and structured using an appropriate emotion scale.

the corresponding author is Olivia Hornung, the lead author is Nora Fteimi and the 3rd author is Stefan Smolnik, they are from the universities of Hagen and Passau in Germany.  Stefan is a research partner of mine but this research comes from his research team at Hagen.....murray


-----Original Message-----
From: Matt Moore <matt@...>
To: main@sikm.groups.io
Sent: Fri, Sep 25, 2020 9:24 pm
Subject: Re: [SIKM] Emotions & KM

What is it about and who is it by?

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 1:28 PM, Murray Jennex via groups.io <murphjen@...> wrote:


my journal has another KM and emotions article coming out in 2021



Stephen Bounds
 

Hi Matt,

Interesting questions. I'd put it this way: affect is the information content which most people receive and process in consistent ways. To judge emotion (including interpretation of affect) requires a mental model of the person's state of mind and projections about likely past and future actions and thus should be treated as a form of knowledge. This is true both of our own self-awareness and our mirrored perspective (ie empathy) for others.

From an organisational and individual perspective, I suggest that emotion, trust, memory, and action are intrinsically linked in lots of complex ways. As Aprill points out, fear leads to a "fight or flight" response which can highly enhance retrieval and formation of short and long term memory. Other emotions are likely similarly linked to physiological changes which will impact on individual and organisational outcomes, although I don't have these to hand.

Any KM effort thus needs to treat accurate predictions about emotional responses of those involved as being as important, if not more important, as the clear communication of the rationale behind the change itself.

Cheers,
Stephen.

====================================
Stephen Bounds
Executive, Information Management
Cordelta
E: stephen.bounds@...
M: 0401 829 096
====================================
On 27/09/2020 10:29 am, Matt Moore wrote:

Hi Stephen,

Thanks for the reference.

“Emotions are neither universal nor located in specific brain regions” - that makes sense to me.

“affect universal and emotion subjective”

Again, this also makes sense. Given human physiology, it would be surprising if elements of emotion weren’t universal. And given that emotion is tied up with our life experience and worldview, it would be surprising if elements of emotion weren’t culturally specific.

So the question is: what does this mean for knowledge managers? Is it simply another aspect of the need for cross-cultural awareness?

Regards,

Matt Moore
+61 423 784 504

On Sep 27, 2020, at 10:11 AM, Stephen Bounds <km@...> wrote:



Hi Matt,

Notwithstanding your commendable attempt to steer clear of jargon, I do note that there's a pretty strong case for considering affect universal and emotion subjective. Dr Barrett has been looking into this for a long time, and her view of the difference is summarised nicely by a reviewer of a recent book:

Emotions are neither universal nor located in specific brain regions; they vary by culture and result from dynamic neuronal networks. These networks run nonstop simulations, making predictions and correcting them based on the environment rather than reacting to it.

More technically, Dr Barrett notes:

Numerous studies find evidence for valence and arousal [ie affect] around the world. When people view abstract visual patterns and describe their aesthetic reactions, they appear to do so universally with valence and arousal. Participants from India (Gujarati), Spain, Vietnam, Hong Kong, Haiti, Greece, China, Croatia, Estonia, Japan, and Poland were asked to judge the similarities and differences between pairs of emotion words. When scientists used statistics (multidimensional scaling) to extract the dimensions of similarity by statistical means, they found both valence and arousal. Valence and arousal also describe the properties of people’s affective feelings in the U.S., Canada, Spain, China, Japan, and Korea. When people from Greece, China, the Netherlands, and of course the US judged the similarity and differences of stereotyped emotion poses of the basic emotion method, similar valence and arousal dimensions were observed to underlie these judgments.

Cheers,
Stephen.
====================================
Stephen Bounds
Executive, Information Management
Cordelta
E: stephen.bounds@...
M: 0401 829 096
====================================
On 27/09/2020 9:04 am, Matt Moore wrote:
Thanks for the references Patrick,

I couldn't access the Mandler one but the Company Command one had this nugget in it: "For many leaders, this is the first time they had experienced these extreme emotions. As a consequence, they learned how to manage these intense emotions, both in themselves and in others. Based on this observation, we argue that any course in crisis leadership should explicitly address the intense emotional component of crisis leadership".

Last year, I was involved in a program to develop innovative ways of teaching ethics to kids. One common technique is scenarios. However one weakness with scenarios (e.g. the now-infamous trolley problem) is that deciding these things hypothetically and in a safe environment is very different to deciding in a real world situation where people may live or die.

BTW I also found this paper on emotion and organizational learning interesting - plus it has a great title: https://www.academia.edu/32900520/Uncomfortable_KnowledgeManagement_The_Impact_of_Emotion_on_Organisational_Learning

Also: I am trying to avoid using the term "affect" as most non-specialists don't know what it means

Regards,

Matt Moore
+61 423 784 504

On Sep 26, 2020, at 3:07 PM, Patrick Lambe <plambe@...> wrote:

Matt - there’s more on emotions in the context of learning - “affect” is the term typically used.

Nate Allen (of Company Command fame) did a study with colleagues on the role of emotional affect in learning and leadership in crisis situations. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.845.7532&rep=rep1&type=pdf

George Mandler did a study on affect, problem solving and memory in the 1980s. The link is to an e-book on affect and mathematical problem solving (educational focus), Mandler's paper is chapter 1 https://d1wqtxts1xzle7.cloudfront.net/63633380/affect_and_mathematical_problem_solving20200615-98668-qo4e09.pdf

P



Patrick Lambe
Partner
Straits Knowledge

phone:  +65 98528511

web:  www.straitsknowledge.com
resources:  www.greenchameleon.com
knowledge mapping:  www.aithinsoftware.com



Matt Moore
 

April,

Completely agree that fear is a significant emotion that we deal with. That's why I asked this last year: https://medium.com/@stangarfield/what-is-the-most-confronting-and-challenging-question-for-the-knowledge-management-community-b109f3eb6992

Perhaps the reason that we so often have to deal with fear is that most organisations are run on it. And many of the fears that people experience in organisations are justified. "Would senior management fire me if they could?" Well, yeah, they probably would. "Will people criticise what I do?" Yip. If they think it will make them look good.

So while I agree, we need to try to allay fears and promote positive messages, we also need to be honest with ourselves. If the incentives (be they explicit or tacit) are against collaboration and knowledge work, a knowledge management program that doesn't tackle these issues is likely to fail. If an organisation is a dangerous place (and many are) then fear is rational. Altho I would absolutely agree that not all fears are rational.

More broadly, I'd say that many managers have an at best partial understanding of the emotional states of their subordinates. Which can be both a strength and a weakness.

Regards,

Matt


On Sun, Sep 27, 2020 at 11:08 AM Aprill Allen <aprill@...> wrote:
One of the most significant emotions we deal with in the KM domain is fear. 

The most primal is fear of being made redundant by giving away knowledge. 

Fear of not being promoted or recognised because someone else will get the credit. 

Fear of being wrong or inadequate by sharing something less than “perfect”. 

Fear of being reprimanded because knowledge capture takes time and impacts my KPIs. 

Fear of loss of prestige, status or bonuses because the compensation structure is aligned with competition rather than collaboration. 

Knowledge managers have to overcome all these by working with leadership (ideally) to communicate the benefits to individuals and teams, to reconnect with common big picture goals and vision, and to rally around a coordinated effort. When belonging and excitement overtake fear, that’s when the big payoffs materialise. 


Murray Jennex
 

I included a fear of job loss with my factors impacting knowledge sharing and KM use many years ago in my research.  In the major study I did it was not significant and that really surprised me.  The reason was the organizational culture which expected knowledge sharing and in particular took steps to not find fault or other possible punishments when people shared, also the personnel evaluation model had shifted from what you knew to make you valuable to how well you shared.  Bottom line is I agree that fear is an important factor, but it can be mitigated....murray jennex


-----Original Message-----
From: Matt Moore <matt@...>
To: main@sikm.groups.io
Sent: Sat, Sep 26, 2020 10:43 pm
Subject: Re: [SIKM] Emotions & KM

April,

Completely agree that fear is a significant emotion that we deal with. That's why I asked this last year: https://medium.com/@stangarfield/what-is-the-most-confronting-and-challenging-question-for-the-knowledge-management-community-b109f3eb6992

Perhaps the reason that we so often have to deal with fear is that most organisations are run on it. And many of the fears that people experience in organisations are justified. "Would senior management fire me if they could?" Well, yeah, they probably would. "Will people criticise what I do?" Yip. If they think it will make them look good.

So while I agree, we need to try to allay fears and promote positive messages, we also need to be honest with ourselves. If the incentives (be they explicit or tacit) are against collaboration and knowledge work, a knowledge management program that doesn't tackle these issues is likely to fail. If an organisation is a dangerous place (and many are) then fear is rational. Altho I would absolutely agree that not all fears are rational.

More broadly, I'd say that many managers have an at best partial understanding of the emotional states of their subordinates. Which can be both a strength and a weakness.

Regards,

Matt

On Sun, Sep 27, 2020 at 11:08 AM Aprill Allen <aprill@...> wrote:
One of the most significant emotions we deal with in the KM domain is fear. 

The most primal is fear of being made redundant by giving away knowledge. 

Fear of not being promoted or recognised because someone else will get the credit. 

Fear of being wrong or inadequate by sharing something less than “perfect”. 

Fear of being reprimanded because knowledge capture takes time and impacts my KPIs. 

Fear of loss of prestige, status or bonuses because the compensation structure is aligned with competition rather than collaboration. 

Knowledge managers have to overcome all these by working with leadership (ideally) to communicate the benefits to individuals and teams, to reconnect with common big picture goals and vision, and to rally around a coordinated effort. When belonging and excitement overtake fear, that’s when the big payoffs materialise. 


Stan Garfield
 

Reminder: New day and time for the October monthly call
This month's call will be held on a special day and time. Our speaker, Matt Moore, would like to include fellow Australians. So the call will start at 5:00 pm US EDT on Monday, October 19, 2020, which is 8:00 am on Tuesday, October 20 in Sydney. Matt's topic will be More Than A Feeling: Knowledge Management & Emotion. Please update your calendars.

The call will held be in Zoom, not using our usual dial-in numbers.