HR Analytics in Perspective: Role of Analytics, Defining HR Analytics, HR Analytics: The Third Wave for HR value creation, HR Measurement journey in tune with HR maturity journey Understanding the organizational system (Lean) , Locating the HR challenge in the system , Valuing HR Analytics in the organizational system, Typical problems (working session)
Markov Chain Analysis in HR Decision Makingrahul23t263
Markov chain is one of the techniques used in operations research with possibilities view that managers faced in organizational decision making .Manpower planning process which the management determines how an Markov Chain move its current manpower position to its desired manpower position.
Through planning, management strives to have the right number and right kinds of people, at the right places at the right time, doing things which result in both the organization and individual receiving maximum long-run benefits.
HR Analytics in Perspective: Role of Analytics, Defining HR Analytics, HR Analytics: The Third Wave for HR value creation, HR Measurement journey in tune with HR maturity journey Understanding the organizational system (Lean) , Locating the HR challenge in the system , Valuing HR Analytics in the organizational system, Typical problems (working session)
Markov Chain Analysis in HR Decision Makingrahul23t263
Markov chain is one of the techniques used in operations research with possibilities view that managers faced in organizational decision making .Manpower planning process which the management determines how an Markov Chain move its current manpower position to its desired manpower position.
Through planning, management strives to have the right number and right kinds of people, at the right places at the right time, doing things which result in both the organization and individual receiving maximum long-run benefits.
David Ulrich is a true HR Management Guru. His HR Model and his HR Roles and Responsibilities changed Human Resources as we know it.
The key HR Roles in the organization are:
HR Business Partner
Change Agent
Administration Expert
Employee Advocate
This HR Roles define the strategic framework for Human Resources Functions all around the Globe. The modern HR Management is defined using these simply defined roles to identify key tasks, goals and objectives for Human Resources in the organization.
David Ulrich defined the basic scope for Human Resources to become a strategic partner for the top executives in the company. The roles are strongly interconnected, but they deliver the real value added to the company, which is seen and valued by both management and employees.
The modern HR Department cannot exist without a well defined HR Model. The HR Model describes how responsibilities are split between HR units and employees in Human Resources. It defines how key HR tasks will be delivered and who will be accountable for the delivery.
Agile HR - Human Resource Management - Manu Melwin Joymanumelwin
The "Agile Model of HR" states that human resources' job is not just to implement controls and standards, and drive execution—but rather to facilitate and improve organizational agility.
HR practitioners have learned to add value by becoming effective facilitators of senior team strategic planning sessions. Operationally, HR units can ensure their plans and programs support and drive strategic business: Capability Assessment, Capacity Management, SWOT-FS, Importance-Performance Analysis, Benchmarking and Best Practice studies and impact evaluation using Kirkpatrick Level 3 & 4 assessment are just some of the tools.
Assessment Centre methodology used to build the talent & leadership pipeline of sales forces was little used until Dr Wilfred Monteiro pioneered the concept and practice in India. A peek at the methodology
Agile HR: Transforming a Human Resources Team Using ScrumSeedbox
At Seedbox Technologies, we use agile development and scrum in all our engineering teams and have the vision of becoming a fully agile company one day. To support this vision, some of our non-engineering teams are starting to adopt and adapt agile principles that will help them deliver more value for our customers, partners, and team members. Here is a kickoff presentation we created to start this transformation with one of our HR teams, responsible for driving our company culture projects. We hope this can inspire other technology (and non-tech) companies to make a similar change in their organizations.
David Ulrich is a true HR Management Guru. His HR Model and his HR Roles and Responsibilities changed Human Resources as we know it.
The key HR Roles in the organization are:
HR Business Partner
Change Agent
Administration Expert
Employee Advocate
This HR Roles define the strategic framework for Human Resources Functions all around the Globe. The modern HR Management is defined using these simply defined roles to identify key tasks, goals and objectives for Human Resources in the organization.
David Ulrich defined the basic scope for Human Resources to become a strategic partner for the top executives in the company. The roles are strongly interconnected, but they deliver the real value added to the company, which is seen and valued by both management and employees.
The modern HR Department cannot exist without a well defined HR Model. The HR Model describes how responsibilities are split between HR units and employees in Human Resources. It defines how key HR tasks will be delivered and who will be accountable for the delivery.
Agile HR - Human Resource Management - Manu Melwin Joymanumelwin
The "Agile Model of HR" states that human resources' job is not just to implement controls and standards, and drive execution—but rather to facilitate and improve organizational agility.
HR practitioners have learned to add value by becoming effective facilitators of senior team strategic planning sessions. Operationally, HR units can ensure their plans and programs support and drive strategic business: Capability Assessment, Capacity Management, SWOT-FS, Importance-Performance Analysis, Benchmarking and Best Practice studies and impact evaluation using Kirkpatrick Level 3 & 4 assessment are just some of the tools.
Assessment Centre methodology used to build the talent & leadership pipeline of sales forces was little used until Dr Wilfred Monteiro pioneered the concept and practice in India. A peek at the methodology
Agile HR: Transforming a Human Resources Team Using ScrumSeedbox
At Seedbox Technologies, we use agile development and scrum in all our engineering teams and have the vision of becoming a fully agile company one day. To support this vision, some of our non-engineering teams are starting to adopt and adapt agile principles that will help them deliver more value for our customers, partners, and team members. Here is a kickoff presentation we created to start this transformation with one of our HR teams, responsible for driving our company culture projects. We hope this can inspire other technology (and non-tech) companies to make a similar change in their organizations.
MULTI-AGENT PARADIGM FOR LEADERSHIP SELECTION: A REVIEWEditor IJMTER
A Multi-agent System (MAS) is comprised of multiple interacting intelligent agents. Agents
in the MAS could all be of same type (homogeneous) or different (heterogeneous). MAS are used to
solve problems which are either difficult for an individual agent to solve or when the problem is
inherently comprised of multiple actors interacting together. However, the nature of MAS design
coordination among agents in MAS is always a core issue. Coordination and cooperation allows the
agents to manage their inter dependencies and the type and nature of interactions. Coordination and
cooperation differ in degree of inter-agent knowledge and beliefs. Agent coordination is usually
achieved in the backdrop of a communication system between agents. This paper is a based on the
review of various work on selection of multi-agent for various task domain.
Requirement analysis, architectural design and formal verification of a multi...ijcsit
This paper presents an approach based on the analysis, design, and formal verification of a multi-agent
based university Information Management System (IMS). University IMS accesses information, creates
reports and facilitates teachers as well as students. An orchestrator agent manages the coordination
between all agents. It also manages the database connectivity for the whole system. The proposed IMS is
based on BDI agent architecture, which models the system based on belief, desire, and intentions. The
correctness properties of safety and liveness are specified by First-order predicate logic.
Evaluating Soft Approaches Used in Strategy Development and Planning by Moh...Mohammad Ali Jaafar
The paper introduces and evaluates six soft approaches used in strategy development and planning. (SWOT analysis, the Future Workshop, the Scenario methodology, Strategic Option Development and Analysis, Strategic Choice Approach and Soft Systems Methodology)
T OWARDS A S YSTEM D YNAMICS M ODELING M E- THOD B ASED ON DEMATELijcsit
If System Dynamics (SD) models are constructed based
solely on decision makers' mental models and u
n-
derstanding of the context subject to study, then the resulting systems must necessarily bear some d
e
gree of
deficiency due to the subjective, limited, and internally inconsistent mental models which led to t
he conce
p-
tion of these systems. As such, a systematic method for constructing SD models could be esse
n
tially helpful
in overcoming the biases dictated by the human mind's limited understanding and conceptualization of
complex systems. This paper proposes a
novel combined method to su
p
port SD model construction. The
classical Dec
i
sion Making Trial and Evaluation Laboratory (DEMATEL) technique is used to define causal
relationships among variables of a system, and to construct the corresponding Impact Relatio
n Maps
(IRMs). The novelty of this paper stems from the use of the resulting total influence m
a
trix to derive the
system dynamic's Causal Loop Diagram (CLD) and then define variable weights in the stock
-
flow chart
equations. This new method allows to overc
ome the subjectivity bias of SD
mode
ling while projecting D
E-
MATEL in a more d
y
namic simulation environment, which could significantly improve the strategic choices
made by an
a
lysts and policy makers
Chapters 4,5 and 6Into policymaking and modeling in a comple.docxtiffanyd4
Chapters 4,5 and 6
Into policymaking and modeling in a complex world
From Building a model to adaptive robust decision- making using systems modelling
Features and added value of simulation Models using different modelling approaches supporting policymaking: A comparative analysis.
Chapter Goals and Objectives Overall – students will learn and understand
consequences of complexity in the real-world, and meaningful ways to understand and manage such situations
the implications of complexity and that many social systems are unpredictable by nature, especially when in the presence of structural change (transitions)
natural tendency to criticize the approaches that ignore difficulties and pretend to predict using simplistic models
that managing a complex system requires a good understanding of the dynamics of the system in question—to know, before they occur, some of the real possibilities that might occur and be ready so they can be reacted to as responsively as possible.
4. Policymaking and modeling in a complex world
the word “complexity” can be used to indicate a variety of kinds of difficulties
identification of complexity and uncertainty in policy-making
in very simple physical systems, interactions may give rise to complex behavior, expressed in different types of behavior, ranging from very stable to chaotic
reasons why complex adaptive systems have a strong capacity to self-organize
two of the ways systems are oversimplified: quantification and compartmentalization
models are assessed by their ability to predict/mirror observed aspects of the environments
5. From building a model to adaptive robust decision-making using systems modeling
System Dynamics Modeling and Simulation of Old
✓ methods for modeling and simulating dynamically complex systems
✓ evolutions in modeling and simulation with recent explosive growth in computational power, data, social media, to support decision-making
Recent Innovations and Expected Evolutions
✓ Why often seemingly more revolutionary—innovations have been introduced and demonstrated, but that they have not been massively adopted yet
Current and Expected Evolutions
✓ Three current evolutions expected to further reinforce - “experiential art” to “computational science.”
Future State of Practice of Systems Modeling and Simulation
✓ modeling and simulation with sparse data to modeling and simulation with (near real-time) big data;
✓ simulating and analyzing a few simulation runs to simulating and simultaneously analyzing well-selected ensembles of runs;
✓ using models for intuitive policy testing to using models as instruments for designing adaptive robust robust policies;
✓ developing educational flight simulators to fully integrated decision support.
Features and added value of simulation models using different modelling approaches to policy-making: A Comparative analysis
Foundations of Simulation Modelling
✓ model simplification definitions—smaller, less detailed, le.
Chapters 4,5 and 6Into policymaking and modeling in a comple.docxmccormicknadine86
Chapters 4,5 and 6
Into policymaking and modeling in a complex world
From Building a model to adaptive robust decision- making using systems modelling
Features and added value of simulation Models using different modelling approaches supporting policymaking: A comparative analysis.
Chapter Goals and Objectives Overall – students will learn and understand
consequences of complexity in the real-world, and meaningful ways to understand and manage such situations
the implications of complexity and that many social systems are unpredictable by nature, especially when in the presence of structural change (transitions)
natural tendency to criticize the approaches that ignore difficulties and pretend to predict using simplistic models
that managing a complex system requires a good understanding of the dynamics of the system in question—to know, before they occur, some of the real possibilities that might occur and be ready so they can be reacted to as responsively as possible.
4. Policymaking and modeling in a complex world
the word “complexity” can be used to indicate a variety of kinds of difficulties
identification of complexity and uncertainty in policy-making
in very simple physical systems, interactions may give rise to complex behavior, expressed in different types of behavior, ranging from very stable to chaotic
reasons why complex adaptive systems have a strong capacity to self-organize
two of the ways systems are oversimplified: quantification and compartmentalization
models are assessed by their ability to predict/mirror observed aspects of the environments
5. From building a model to adaptive robust decision-making using systems modeling
System Dynamics Modeling and Simulation of Old
✓ methods for modeling and simulating dynamically complex systems
✓ evolutions in modeling and simulation with recent explosive growth in computational power, data, social media, to support decision-making
Recent Innovations and Expected Evolutions
✓ Why often seemingly more revolutionary—innovations have been introduced and demonstrated, but that they have not been massively adopted yet
Current and Expected Evolutions
✓ Three current evolutions expected to further reinforce - “experiential art” to “computational science.”
Future State of Practice of Systems Modeling and Simulation
✓ modeling and simulation with sparse data to modeling and simulation with (near real-time) big data;
✓ simulating and analyzing a few simulation runs to simulating and simultaneously analyzing well-selected ensembles of runs;
✓ using models for intuitive policy testing to using models as instruments for designing adaptive robust robust policies;
✓ developing educational flight simulators to fully integrated decision support.
Features and added value of simulation models using different modelling approaches to policy-making: A Comparative analysis
Foundations of Simulation Modelling
✓ model simplification definitions—smaller, less detailed, le ...
Ijcsit12REQUIREMENTS ENGINEERING OF A WEB PORTAL USING ORGANIZATIONAL SEMIOTI...ijcsit
The requirements of software are key elements that contribute to the quality and users satisfaction of the
final system. In this work, Requirements Engineering (RE) of web sites is presented using an organizational
semiotics perspective. They are shown as being part of an organization, with particular practices, rules
and views considering stakeholders several differences and opinions. The main contribution of this paper is
to relate an experience, from elicitation to validation, showing how organizational semiotics artifacts were
exploited in a collaborative and participatory way to RE of a web portal. A case study is described in order
to demonstrate the feasibility of using such artifacts to RE when we think about the system as being part of
a social organization.
The series of presentations contains the information about "Management Information System" subject of SEIT for University of Pune.
Subject Teacher: Tushar B Kute (Sandip Institute of Technology and Research Centre, Nashik)
http://www.tusharkute.com
The Evaluation of Generic Architecture for Information Availability (GAIA) an...inventionjournals
Along with the growing interest in agent applications, there has been an increasing number of agentoriented software engineering methodologies proposed in recent years. These methodologies were developed and specially tailored to the characteristics of agents. The roles of these methodologies can provide methods, models, techniques, and tools so that the development of agent based system can be carried out in a former and systematic way. The goal of this paper is to understand the relationship between two key agent-oriented methodologies: Gaia, and MaSE. More specially, we evaluate and compare these three methodologies by performing a feature analysis, on them, which is carried out by evaluating the strengths and weaknesses of each participating methodology using an attribute-based evaluation framework. This evaluation framework addresses some areas of an agent-oriented methodology: concepts, modeling language, process and pragmatics
The Evaluation of Generic Architecture for Information Availability (GAIA) an...inventionjournals
Along with the growing interest in agent applications, there has been an increasing number of agentoriented software engineering methodologies proposed in recent years. These methodologies were developed and specially tailored to the characteristics of agents. The roles of these methodologies can provide methods, models, techniques, and tools so that the development of agent based system can be carried out in a former and systematic way. The goal of this paper is to understand the relationship between two key agent-oriented methodologies: Gaia, and MaSE. More specially, we evaluate and compare these three methodologies by performing a feature analysis, on them, which is carried out by evaluating the strengths and weaknesses of each participating methodology using an attribute-based evaluation framework. This evaluation framework addresses some areas of an agent-oriented methodology: concepts, modeling language, process and pragmatics
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Leading Change strategies and insights for effective change management pdf 1.pdf
Interpretive structural modeling
1. Interpretive Structural Modeling
Dr. G. P. Sahu
(Assistant Professor – Information Systems)
School of Management Studies
Motilal Nehru National Institute of Technology, Allahabad.
July 25, 2008
1
2. Interpretive Structural Modeling
Interpretive Structural Modeling is used for
identifying and summarizing relationship
among specific variables, which define a
problem or an issues.
It is an interactive learning process.
2
3. Objective of ISM
• To identify and rank the variables.
• To establish the interrelationship among the
variables.
• To discuss the managerial implication of the
research.
3
4. Steps of ISM Methodology
1. Variables affecting the system under consideration
are listed.
2. The Structural Self Interaction Matrix (SSIM) is
developed for the variables.
3. Reachability Matrix is developed from the SSIM.
4. Reachability Matrix obtained in step 3 is partitioned
into different level.
5. Finally the hierarchies of the variables are formed.
4
6. Variables affecting Information and
Communication Technology adoption in SME.
Sl. Variables
No.
Supporting Studies
1
Relative Advantage
Lee and Runge (2001). Khazanchi
(2005); Seyal and Rahman (2003).
2
Social Expectation
Lee and Runge (2001). Khazanchi
(2005); Seyal and Rahman (2003).
3
Firm’s Innovativeness
Lee and Runge (2001); Winston and
Dologite (1999); Khazanchi (2005);
Seyal and Rahman (2003).
4
Management Attributes
Seyal and Rahman, (2003); Jeon
et.al.(2006); Chahal and Kohali
(2006).
6
7. Variables affecting Information and
Communication Technology adoption in SME.
Sl. Variables
No.
Supporting Studies
5
Organisational Attributes
Seyal and Rahman (2003);
Levenburg and Klein (2006).
6
Adoption Attributes
Seyal and Rahman (2003); Jeon
et.al. (2006),
7
End User experience
Winston and Dologite(1999).
8
Owner knowledge
Winston and Dologite (1999);
Ihlstrom and Nilsson (2003);
Seyal and Rahman (2003);
Wymer and Regan (2005).
7
8. Variables affecting Information and
Communication Technology adoption in SME.
Sl. Variables
No.
9
Extra organizational
situation
Supporting Studies
Winston and Dologite(1999);
Khazanchi (2005).
10 Government Support
Jeon et.al. (2006); Wymer and
Regan (2005); Jeon et.al. (2006);
Wymer and Regan (2005).
11 Financial Resource
Levenburg and Klein (2006);
Khazanchi (2005)
8
9. Relative Advantage
Social Expectation
Firm’s Innovativeness
Management Attributes
Organisational Attributes
Usage of Information
and Communication
Technology
Adoption Attributes
End User experience
Owner’s knowledge
Extra organizational situation
Government Support
Financial Resource
9
10. Interpretive Structural Modeling
•
•
•
•
Personal interview is conducted of the two experts, one is
academician and the other entrepreneurship consultant. It is
asked them to establish the relationship between the various
factors as follows:
A, If ‘i’ is predictor of ‘j’.
B, If ‘j’ is predictor of ‘i’.
C, If ‘i’ and ‘j’ predict each other.
D, If no predict each other.
10
11. Structural Self Interaction Matrix
(SSIM)
ISM methodology suggest the use of expert
opinions based on the various management
technique in developing the contextual
relationship among the variables.
11
12. Structural Self-Interaction Matrix (SSIM)
Elements
11 10
9
8
7
6
5
4
3
2
A
1
Relative Advantage
A
A
A
D
D
B
A
A
A
2
Social Expectation
A
A
A
A
D
A
A
A
D
3
Firm’s Innovativeness
D
D
D
D
D
D
A
D
4
Management Attributes
A
B
D
A
D
A
A
5
Organizational Attributes
A
D
A
A
D
A
6
Adoption Attributes
B
D
D
A
D
7
End User experience
B
A
A
A
8
Owner knowledge
A
D
D
9
Extra Org. situation
B
D
10
Government Support
D
11
Financial Resource
12
13. Reachability Matrix
• A, If ‘i’ is predictor of ‘j’, then (i,j) is 1 and (j,i)
is 0
• B, If ‘j’ is predictor of ‘i’ then (j,i) is 1 and (i,j)
is 0
• C, If ‘i’ and ‘j’ predict each other then (i,j) is 1
and (j,i) is 1
• D, If no predict each other then (i,j) is 0 and
(j,i) is 0
13
17. Level of Variables
Level of variables are determined on the
basis of intersection of Reachability Set
and Intersection Set
17
18. Level of Variables
Variable
Reachability
Set
Antecend Intersection Set
Set
Level
1
1,2,3,4,5,9,10,11
1,6
1
VII
2
2,4,5,6,8,9,10,11
1,2
2
VI
3
3,5
1,3
3
II
4
4,5,6,8,11
1,2,4,10
4
IV
5
5,6,8,9,11
1,2,3,4,5
5
III
6
1,6,8,
2,4,5,6,10
6
III
7
7,8,9,10
7,11
7
III
8
8,11
2,4,5,6,7,8
8
II
9
9
1,2,5,7,9,11
9
I
10
4,6,10
1,2,7,10
10
V
11
7,9,11
1,2,4,5,8,11
11
II
18
19. Variable Hierarchy
Extra Organizational
Situation (9)
Firm’s Innovativeness (3)
Owner knowledge (8)
Financial Resource (11)
Organizational Attributes (5)
Adoption Attributes (6)
End User experience (7)
Management Attributes (4)
Government Support (10)
Social Expectation (2)
Relative Advantage (1)
19