1 ROI CALCULATION AND BUSINESS CASE 1ROI CALCULATION AND BUSIN.docx

1 ROI CALCULATION AND BUSINESS CASE 1
ROI CALCULATION AND BUSINESS CASE 3
ROI of Implementation
Katherine Askew
CMGT/583
2 March 9, 2020
David Conway
This research paper mostly focuses on the calculation of Return
on Investment in Phoenix Fine Electronics enterprise; it also
covers the overall needs and desires outcomes of the business.
The scope of the project, measurable values of the new system,
description of the latest strategies and recommending either
continue or stop with project establishment; all concepts
described below.
3 High-level overall business needs and desired outcomes
Business needs refer to the gaps found in the current business
and its objectives. The most important driving factors in most
enterprises are business or enterprise needs. We have so many
different types of needs; some of them include talent,
infrastructure, facilities, systems, applications, and many more.
For Phoenix enterprise to succeed, it should focus on several
business needs that can help it accelerate and speed up the
achievement of its goals. Here are some examples of business
needs that should be met for the enterprise to acquire the
desired outcome.
Clients. The enterprise has a responsibility of satisfying
customers by providing them with suitable and needed goods
and services(Yeganeh, 2019). Despite maintaining and retaining
customers, it is its responsibility of the company to bring in
new clients to enhance the expansion and growth of the
company hence the need for the company to locate and bring in
the right customers for product purchase and maximizing
profits. Through having the right audience, the enterprise will

be able to build a scalable business that will lead to better
results.
4 Retention of employees. Despite ensuring that the business
has a continuous flow of clients, having consistent employees to
work on the proposed project is a great deal. Creates the need
for the enterprise to ensure that it has steady workers who can
aid in carrying out general enterprise tasks, working on
products to improve them, and giving customer services, care,
and help. Doing these will reduce the business turnover hence
easier to manage.
Marketing Phoenix enterprises should make sure that they are
conversant with the essential roles of marketing in an
organization. They should always work to ensure that any
marketing strategy employed is always equated to profit;
however difficult it may be for an excellent strategized plan,
and planned advertisement budget for thriving both online and
offline.
5 Scope of the project
The scope of this project is to help Phoenix Fine Electronics
maximize and increase profits by increasing sales and also
increasing the number of customers present. Companies
achieved this by expanding business through investing and
building other new business in different locations. For example,
when Phoenix Fine Enterprises decides to initiate and
implement its newly suggested project of investing in three
separate stores of good five years, the projected end goal of this
plan is to generate higher revenue compared with the past.
Customer satisfaction. Since Phoenix Fine Electronic has a
large population of customers in the current stores, opening
other branches will help it reduce congestion during service
provision hence satisfying customers’ wants. Through doing
this, the enterprise will be able to hook customers’ trust,
therefore, turning into loyal customers of an organization.
Job creation. Opening of the other three stores by Phoenix Fine
Electronics creates room for new job employment. Through this,
jobs are created, such as store manager and Information

Technology, which on the other side, help in curbing the
employment crisis. 6 The IT manager is responsible for
managing the IT systems, making decisions on what technology
and software are needed, and implementing the systems while
ensuring accurate reporting to the primary office. 7 The store
manager is responsible for all staffing, inventory, and sales
functions within the store.
Proper utilization of technology. Phoenix Fine should ensure
structured information technology plans for supporting stores,
increasing sales, inventory tracking, secure store customer data;
perform payroll; 7 and report all sales, inventory, and payroll
data to the primary office.
8 To hire Chief Financial Officer and Chief Information
Officer. 6 The CFO will manage the company finances for
development. The CIO will manage the consolidation of the
different systems and technologies that exist between the stores,
streamline the information gathering and reporting to the main
office, and develop an online presence that will catapult the
company into a competitive position on a national level.
Measurable Values
Introduction Phoenix Fine Electronics, being one of those
organizations doing well, needs to be incorporated by different
departments to increase its productivity. 9 Furthermore, the
decisions made by one head of department also influence the
other departments. Due to this understanding, the chief
information officer affects the establishment of management
plans and needs. However, there is a need for collaboration
between the chief financial officers and the chief information
officer to incorporate the functions of the ERP system. The
roles of the mentioned systems help in the expansion of the
organization’s branches and client base. The desired results
from the incorporation depend on the seriousness of the
functions and the implementation level (Mehta, 2016). Among
the desired results is securing customer satisfaction scorecard
that will enhance the expansion of the new
establishments. Also, the organization will have a well laid-out

plan when it comes to the development of the branches, as well
as the resources needed.
Moreover, the other outcome is increased profits due to
increased sales. The success of the system hinges on the results
achieved and on the flow of the functions. A sufficient flow of
outcomes leads to the achievement of the outcomes hence the
success of the system.
The Current Project Phoenix Fine Electronics has several
stores; each store employs an IT manager and a store manager
who reports to the chief executive officer. The organization has
an IT project that focuses on utilizing technology in the
store; the expected benefits include an increase in sales,
tracking inventory, securing customer data, reporting all sales,
payroll data, and account to the primary office. The IT manager
in the organization is mandated to manage the IT system and
make decisions related to technology in the organization. 7 The
store manager is responsible for inventory, sales, and staffing
functions within the store. 9 Due to the nature of the IT project,
the chief executive officer is concerned about the aggregation of
departmental and customer data to enable the organization to
make timely and better business decisions. However, because
the CEO is not knowledgeable about IT-related issues, the
organization hired the chief information officer and the chief
financial officer to oversee the organization’s finances and
expansion. The two new employees are required to monitor the
systems and technologies that exist between the different stores,
streamline the process of gathering information, and to report to
the headquarters.
Organizational Values Brought by the System Due to the
benefits of the system to the organization, three outcomes
would arise because of using the system. They are; 9 increased
customer satisfaction scorecard that will lead to expansion of
the customer base, good plan for the development of the
branches, and increased profits due to increased sales. The three
benefits lead to the following organizational values · Cherishing
customer satisfaction · Well-planned expansion strategy ·

Increasing organizational performance Cherishing customer
satisfaction With cherishing customer satisfaction, the system
enables the organization to be rated by the different customers
that use its products. The feedback and reviews by customers
allow potential customers to assess the quality of the products
offered by the organization hence attract more
customers. Furthermore, the positive feedback from clients is
beneficial, particularly to the new stores that need to attract
many new customers. Based on the input, the organization may
strategize on ways of improving customer satisfaction.
Well-planned Expansion Strategy The organization will
establish an expansion strategy useful for the current
situation. A well-planned expansion strategy will ensure that
adequate resources allocated to the new stores. Furthermore, it
will streamline the linkage between the headquarters and the
new stores such that inventory is sufficient to meet the demand
at the new stores.
Improving Organizational Performance The system will lead to
improved organizational performance because of increased
efficiency in inventory control, communication with the
headquarters, and prompt feedback from customers. All
organizations value performance because it enhances their
competitive advantage; therefore, the new system will be a
source of competitive advantage that will lead to higher profits
Benefits of the Values to the Organization The above three
mentioned organizational values that will arise a result from
adopting the system are beneficial to the organization because it
is a source of competitive advantage. Notably, the competitive
advantage of the organization lies in the ability of the
organization to use the existing resources to achieve the desired
outcomes cost-effectively (Lahovnik & Breznik, 2014). As a
source of competitive advantage, the organization will penetrate
the market in the new locations without investing heavily in
marketing.
Effective planning for expansions helps the organization to
optimize the available processes and resources to maximize

output. That means the organization can expand without
substantial capital investment because of the optimization of
processes. To increased organizational performance, the system
is beneficial because the higher the profits, the higher the rate
of return on investment. The high rate of return on investment
attracts investors to the organization. The money from investors
helps the organization to expand to new geographical regions
and products offered.
How the Values will differentiate the Business to Customers
The organizational values differentiate one organization from
the other. However, by adopting the system, the communication
between the different stores and the organization’s headquarters
will be expanded. Furthermore, the system will enhance the
internal capabilities of Phoenix Fine Electronics in terms of
customer relations management. One of the differences that will
arise due to the values resulting from the use of the system is
enhanced customer relations management. The organization will
be known for being customer-focused because the feedback
received from the system will influence the decisions made in
terms of service delivery and product innovation (Lahovnik &
Breznik, 2014). The customer base will differentiate from
others based on the promptness with which it addresses their
concerns. The system enables a connection between the business
and the customers; therefore, the concerned employees within
the company will be able to receive clients’ interests and
respond to them promptly (Lahovnik & Breznik, 2014).
Risks of Doing the Project Engaging in the project has some
underestimated risks. As an IT-oriented system, there is a risk
of not achieving the desired outcomes in terms of
performance. According to Lahovnik and Breznik (2014),
information technology may not attain the desired results in
terms of organizational performance; therefore, the organization
invests heavily in IT but receives little in return. That means
among the risks of adopting the system is a higher amount on
investment and a lower rate of return on investment due to the
lack of changes in organizational performance.

Furthermore, the project may face resistance from the
organization’s employees. Resistance arises when there is
inadequate preparedness for change. Resistance may lead to a
boycott of the system leading to non-performance. Furthermore,
the system will lead to a collection of vast customer and
employee data. The privacy of the data may be a breach by the
cybercriminals who may sell the data to the organization’s
competitors or use it for other malicious activities. For instance,
they may use a customer’s financial information to defraud
them.
Risks of Not Doing the Project Creative and innovative products
and processes as a way of reducing costs, increasing efficiency
and attracting more clients mar the current business
environment. Therefore, not carrying out the project means that
the organization will be stagnant; it will not be able to handle
the changes in the business environment. For example, the
organization will not be to gather and respond to the different
customer concerns on time; as such, the challenge reduces its
competitive advantage and loses its market share to competitors
that adapt technology (Lahovnik & Breznik 2014).
Strategic Alignment
Strategic alignment refers to the process done to make sure that
the strategies enacted are in place. Phoenix Fine Electronic
strategic alignment will ensure concerns raised by the
shareholders, workers, and other concerned bodies of the
enterprise are functioning accurately. Achieving business goals
on time will ensure business plans have their proper strategies,
which lead to success when well executed and implemented.
Strategic alignment helps in easing employee workload by
ensuring that employees that work with only stated
strategies(Thompson, 2017). Since some employees and other
staff members of Phoenix Fine Electronic may not understand
well the suggested strategies, aligning them makes it easier for
them to follow and provide positive or intended feedback.
Proper strategic alignments help businesses in achieving their
set goals in a secure and timely mode.

Estimated ROI and productivity (from Part 1) ROI is the short
form of Return on Investment. It is mostly carried out by both
big and small business enterprises to help them make decisions
on the next type of business they should invest in them.
Through the information provided by ROI, team businesses can
decide to either invest in the new company or not. Below is the
ROI calculation of Phoenix Fine Electronics basing on the
information earlier provided in week one.
ROI = Net Profit / Total Investment * 100
Revenue=$15 million for 25 stores
If 25 stores generate revenue of $15 million for one year, what
about (1) one store?
(1 x 15)/25=0.6m
1 store = 0.6m 0.6x100=60% 60%=0.6
100%=? 100 x 0.6/60=1m
ROI=(0.6/1)x 100%=60% The return on investment per year=
60% Final recommendations
I highly recommend that shareholders of Phoenix Fine
Electronics should invest and expand more on the business
sense, according to the RIO analysis, shareholders will enjoy
more and good profit with a fully implemented plan.
Implementing this project will highly help in solving the
unemployment crisis in the world hence saving the lives of
many people. People such as Information Technology managers,
stock managers, Chief Financial Officer (CFO), and Chief
Information Officer will be able to secure employment. Faster
execution and implementation of the project will help Phoenix
Fine Electronics to utilize its population as early as possible. I
also recommend that Phoenix Fine Electronics should embrace
and practice business needs in its projects.
References
9 Lahovnik, M and Breznik, L (2014), Technological Innovation
Capabilities as a Source of Competitive Advantage: a Case
Study from the Home Appliance Industry. Transformations in
Business & Economics, Vol. 13, No 2 (32), pp. 144-160
9 Mehta, A (2016). BI, SCM, CRM, and ERP in a Nutshell and

their Relationship. Medium. Web. 9 Accessed on 16/2/2020.
Thompson, J. (2017). 10 Principles of Marketing. 4 New York,
NY: 10 Larsen and Keller Education.
Yeganeh, K. (2019). 11 Major Business and Technology Trends
Shaping the Contemporary World (1st ed.). 4 New York,
NY: 11 Business Expert Press.
https://www.essaysforu.com/it-business-partnership/IT Business
Partnership
Citations (11/11)
1. 1Another student's paper
4.
4https://scholarworks.waldenu.edu/cgi/viewcontent.cgi?article=
8414&context=dissertations
Running head: PHOENIX FINE ELECTRONICS 1
PHOENIX FINE ELECTRONICS 2

PHOENIX FINE ELECTRONICS
Katherine Askew
CMGT/583
March 2, 2020
David Conway
SWOT Analysisa) Build
Strengths
· The Phoenix fine electronics company has a large consumer
base, from which components and functionalities of the
information system derives. Comment by Spraggins,
Katherine:
· The stores are in dense retail customer regions, which makes it
easy to capture the needs of the retail customers regarding what
interactions they desire from the system.
· It has mastered the market where its store is, hence the need to
expand with specific interests captured in the built information
system implemented.
· It boasts an agile market research strategy that exploits the
need of its retail customers, thereby earning a significantly high
annual revenue in sales. By building its own information
system, the objectives of the Phoenix Fine Electronics company
are best integrated.
Weaknesses
· Operating on a distributed business model increases costs,
especially when there is an elite resource allocation for the
different stores.
Opportunities
· In the case that a transaction processing system specific to the
business needs of the Phoenix Fine Electronics company,
developed and implemented, interfaced with a management
information system to acquire more in-depth information on
consumer trends, used to boost the managerial skills of the sales

managers.
Threats
· A computing-intensive environment poses cyber-attack risks
on corporate resources such as electronic data generated. Any
flaws within the developed system, which primarily comprises a
vast scope than for a purchased system, lead to expensive
outcomes.b) Buy
Strengths
· Implementing a customized information system significantly
reduces the time spent in software development.
· Information systems fitted with security controls at various
designations prevent the possibility of a successful cyberattack.
· Bought systems are liable to modifications and security
patches that improve the user experience and are usually offered
free of charge.
Weaknesses
· The bought systems may not provide the range of
functionalities that are desirable by the Phoenix Fine
Electronics company to fulfill its business needs.
Opportunities
· By adopting systems that are standardized to meet the
requirements expressed by various regulations, both national
and international, the Phoenix Fine Electronics company
acquires certification, which increases its ratings.
Threats
· Bought systems provide similar security flaws across all
platforms, which can be utilized by intruders and malicious
people to enact cyberattacks.
Guide for determining whether to buy or buildI. Steps towards
Purchasing or building a system in-house
Figure 1:Steps in purchasing or building in-house
Before embarking on deciding whether to buy or build a system
in-house, it is necessary to weigh benefits incurred against
accrued limitations. A purchased system will facilitate a fast
transition for collaborating infrastructure, the supply chain, the

customer base, and the distribution network t ensure the
business springs on its feet in a competitive market with
minimal time wastage. The disadvantage of purchasing a system
is that it is considered the intellectual property of others; hence,
little or no flexibility for tailoring the policy to suit the
business needs. Next is weighing all costs. A comparison to
establish which convention achieves more significant economies
of scale. The second-last item on the list when expanding the
need to purchase or build a system in-house is to know your
business. Understanding your business entails setting the
management framework in shape to allow a smooth transition of
the expansion to include a purchased system or in-house one.
Lastly, make the verdict on whether to buy or build the system
in-house. Where the management does not relish in the idea of
the fear of the unknown, the system should develop in-house to
capture all necessary functions that the business anticipates it to
render (Zhao et al., 2019).
II. Budget considerations
The budget considerations regard a benefit-cost analysis where
the outcome of the integration of a system in a business
environment weighed against costs incurred. The main objective
is towards deriving the increase in the value of the business
when the system is incorporated against it when it was not
present.III. Staffing considerations
There is a need to assess whether a possibility arises where
newly recruited employees support the system. These are
dedicated employees whose sole function is to provide technical
support functionalities, e.g., IT staff. It is also essential to
assess the complexity of a system to determine if training is
required. Depending on the completeness of the business
functions that match the tasks which a system provides, it is
necessary to assess if it is needed to outsource specific business
processes not accounted for within the system (Turekulova et
al., 2016).
Figure 2:Employee considerationsIV. Time considerations

The most critical time consideration regards how long it will
take to integrate the desired system into Phoenix Fine
Electronics’ business model. There is plenty of time utilized in
the implementation phase of the system development life cycle,
production impacts dedicated employees to integrate the system
into the business.V. Risks
The main risk in incorporating a system into the business
environment is that systems are susceptible to malicious attacks,
and middle to high-end institutions are the ones targeted.
Another threat is that an implemented system may not be
compatible with a business model, thereby complicating
business processes.VI. Maintenance plan
Maintenance, oriented towards installing security patches,
upgrading the system components, and integrating new
functionalities, especially where the system is in-house.
VII. References
Turekulova, D., Zumanova, B., Anafiyayeva, Z., Satkanova, R.
S., Zhanakova, N., Nurgaliyeva, Z., & Tuzubekova, M. (2016).
Outsourcing Strategy Development in JSC «PC «KTZ.»
International Journal of Economic Perspectives, 10(3).
Zhao, C., Yang, E., Nie, Y., & Russo, J. D. (2019). Facility
decision making process with a modified value engineering
approach. Journal of Corporate Real Estate.
Running head: SOURCING PLAN
1
SOURCING PLAN
5
Sourcing Plan

Katherine Askew
CMGT/583
February 24, 2020
David Conway
Sourcing Plan
In this paper, we are going to apply the strategic source
planning to guide Phoenix Fine Electronics to adapt the
enterprise solution to the challenges faced by the enterprise.
Phoenix Fine Electronic (PFE) enterprise is a company that
deals with the selling of electronic products to retail customers.
The company has around 25 stores in two states. Each store
serves an approximate population of 100,000. Every town has
approximately three stores where each store has a store and an
Information Technology manager who reports directly to the
Chief Executive Officer (CEO).
Current Technology in the Company
Currently, the information technology plan of the organization
is specific for each store. Even though each of the stores
utilizes the technology that increases the sales, performs
payroll, report sales, track inventory, and payroll data, among
others, each store manager is responsible for the staffing, sales
functions, and the inventory. Evach store for the company is
independent and manages on its own. The information
technologies at each store cannot be accessed directly by the
Chief Executive Officer. It implies that the store manager has to
report to the CEO concerning the different functions and the
activities going on in the organization.
Major Issues with the Technology
Every store carries out activities independently and reports to
the manager daily. There are reservations on how data comes
together and the ability to be accessed by the CEO. The
accumulation of such data together is the major issue that is
affecting the organization. The CEO needs the customer data
combined so that it enables the company to make timely and

better decisions.
Another issue that is facing the organization is the online
presence that will make the organization have a better position
at the national level. The company needs an online presence,
which will enable it to acquire more customers and overcome
competitive advantages.
New Technologies to be Implemented
The implementation of different technologies in an organization
will help overcome the online presence challenges and the
overseeing of the data at various stores. The first technology to
be used is the decentralization of the data. In this instance, a
single entity does not control the data, and the CEO can see all
the activities created on the data (Nasdaq 2017). Meaning all of
the customers’ data collected enables the company to make
timely, better decisions. The appropriate arrangements are faster
by the fact that decision making and planning are distributed,
and the CEO makes the final decision.
Another technology to be implemented is an online store. An
online store is a website or an application where the goods and
services sold over the internet. This technology will highly help
in the development of the online presence of the company as
well as increasing the competitive position to the national level
(Duarte et al., 2018). Through this, most of the products will be
available over the internet, which is also a form of
advertisement. Also, the customers will be giving their views
about specific products, which will help in increasing their
competitive position.
How it addresses the current issues
The decentralization of data will help in addressing the current
issue by putting all the data together. With this, all the customer
data will be able to be accessed by the CEO. Besides,
decentralization makes the process of decision making and
planning easier and faster hence timely decisions in the business

(Liu et al., 2018). On the other hand, the online store will help
in creating a highly competitive advantage to the national level
as the products will be accessed by a broader geographical
region through the internet (Duarte et al., 2018).
Additional advantages or value-added
The technology of data decentralization and an online store will
have an added value to the organization as they both help in
saving time, accountability, and transparency (Liu et al., 2018).
Besides, the online store will also create more awareness of the
products hence marketing them to a national level increasing the
conveniences (Duarte et al., 2018). Besides, they both increase
safety while reducing the input cost.
Approximate time frame to implement the technology
The approximate time will be taken to implement this
technology is approximately 7 (28 weeks) months. The
following table shows the distribution of the data in every
activity.
Time in days
Number of weeks
Data collection
3 weeks
preliminaries
5 weeks
Design
5 weeks
Construction
11 weeks
Implementation
4 weeks
Any dependencies that the company does not currently have to
implement
Other dependencies needed by the company that they presently
do not have. They include:
i. A more massive database - this is where all the data is
decentralized.
ii. Website personnel - he will be in charge of the online store

or website, making sure it is always up to date.
References
Duarte, P., e Silva, S. C., & Ferreira, M. B. (2018). How
convenient is it? Delivering online shopping convenience to
enhance customer satisfaction and encourage e-WOM. Journal
of Retailing and Consumer Services, 44, 161-169.
Liu, J., Li, B., Chen, L., Hou, M., Xiang, F., & Wang, P. (2018,
June). A data storage method based on blockchain for
decentralization DNS. In 2018 IEEE Third International
Conference on Data Science in Cyberspace (DSC) (pp. 189-
196). IEEE.
Nasdaq. (2017). What Does Decentralization Actually Mean?
Retrieved from: https://www.nasdaq.com/articles/what-does-
decentralization-actually-mean-2017-10-16
Measurable Values
Measurable Values
Katherine Askew
CMGT/583
February 17, 2020
David Conway

Measurable Values
Introduction
Phoenix Fine Electronics, like other organizations,
requires the interlink between the different departments as a
way of optimizing productivity and increasing efficiency.
Furthermore, the decisions made by one head of department also
influence the other departments. Due to this understanding, the
chief information officer affects the establishment of
management plans and needs. However, there is a need for
collaboration between the chief financial officers and the chief
information officer to incorporate the functions of the ERP,
CRM, and DSS. The functions of the mentioned systems help in
the expansion of the organization’s branches and client base.
The desired results from the incorporation of the functions of
the systems depend on the seriousness of the functions and the
implementation level (Mehta, 2016). Among the desired results
is securing a customer satisfaction scorecard that will enhance
the expansion of the new establishments. Also, the organization
will have a well laid-out plan when it comes to the expansion of
the branches, as well as the resources needed.
Moreover, the other outcome is increased profits due to
increased sales. The success of the system hinges on the results
achieved and on the flow of the functions. As such, a sufficient
flow of outcomes leads to the achievement of the outcomes
hence the success of the system.
The Current Project
Phoenix Fine Electronics has several stores; each store
employs an IT manager and a store manager who reports to the
chief executive officer. The organization has an IT project that
focuses on utilizing technology in the store; the expected
benefits include an increase in sales, tracking inventory,
securing customer data, reporting all sales, payroll data, and
inventory to the primary office. The IT manager in the

organization is mandated to manage the IT system and make
decisions related to technology in the organization while the
store manager is responsible for inventory, sales, and staffing
functions within the store. Due to the nature of the IT project,
the chief executive officer is concerned about the aggregation of
departmental and customer data to enable the organization to
make timely and better business decisions. However, because
the CEO is not knowledgeable about IT-related issues, the
organization hired the chief information officer and the chief
financial officer to oversee the organization’s finances and
expansion. The two new employees are required to monitor the
systems and technologies that exist between the different stores,
streamline the process of gathering information, and to report to
the headquarters.
Organizational Values Brought by the System
Due to the benefits of the system to the organization,
three outcomes would arise because of using the system. They
are; increased customer satisfaction scorecard that will lead to
expansion of the customer base, good plan for the development
of the branches, and increased profits due to increased sales.
The three benefits lead to the following organizational values
· Cherishing customer satisfaction
· Well-planned expansion strategy
· Increasing organizational performance
Cherishing customer satisfaction
With cherishing customer satisfaction, the system enables
the organization to be rated by the different customers that use
its products. The feedback and reviews by customers allow
potential customers to assess the quality of the products offered
by the organization hence attract more customers. Furthermore,
the positive feedback from clients is beneficial, particularly to
the new stores that need to attract many new customers. Based
on the input, the organization may strategize on ways of
improving customer satisfaction.
Well-planned Expansion Strategy
The organization will establish an expansion strategy

useful for the current situation. A well-planned expansion
strategy will ensure that adequate resources allocated to the new
stores. Furthermore, it will streamline the linkage between the
headquarters and the new stores such that inventory is sufficient
to meet the demand at the new stores.
Improving Organizational Performance
The system will lead to improved organizational
performance because of increased efficiency in inventory
control, communication with the headquarters, and prompt
feedback from customers. All organizations value performance
because it enhances their competitive advantage; therefore, the
new system will be a source of competitive advantage that will
lead to higher profits
Benefits of the Values to the Organization
The above three mentioned organizational values that will
arise a result from adopting the system are beneficial to the
organization because it is a source of competitive advantage.
Notably, the competitive advantage of the organization lies in
the ability of the organization to use the existing resources to
achieve the desired outcomes cost-effectively (Lahovnik &
Breznik, 2014). As a source of competitive advantage, the
organization will penetrate the market in the new locations
without investing heavily in marketing.
Effective planning for expansions helps the organization to
optimize the available processes and resources to maximize
output. That means the organization can expand without
substantial capital investment because of the optimization of
processes. To increased organizational performance, the system
is beneficial because of the higher the profits, the higher the
rate of return on investment. The high rate of return on
investment attracts investors to the organization. The money
from investors helps the organization to expand to new
geographical regions and products offered.
How the Values will differentiate the Business to Customers
The organizational values differentiate one organization
from the other. However, by adopting the system, the

communication between the different stores and the
organization’s headquarters will be expanded. Furthermore, the
system will enhance the internal capabilities of Phoenix Fine
Electronics in terms of customer relations management. As
such, one of the differences that will arise due to the values
resulting from the use of the system is enhanced customer
relations management. The organization will be known for
being customer-focused because the feedback received from the
system will influence the decisions made in terms of service
delivery and product innovation (Lahovnik & Breznik, 2014).
The customer base will differentiate from others based on the
promptness with which it addresses their concerns. The system
enables a connection between the business and the customers;
therefore, the concerned employees within the company will be
able to receive clients’ interests and respond to them promptly
(Lahovnik & Breznik, 2014).
Risks of Doing the Project
Engaging in the project has some underestimated risks. As
an IT-oriented system, there is a risk of not achieving the
desired outcomes in terms of performance. According to
Lahovnik and Breznik (2014), information technology may not
attain the desired results in terms of organizational
performance; therefore, the organization invests heavily in IT
but receives little in return. That means among the risks of
adopting the system is a higher amount on investment and a
lower rate of return on investment due to the lack of changes in
organizational performance.
Furthermore, the project may face resistance from the
organization’s employees. Resistance arises when there is
inadequate preparedness for change. Resistance may lead to a
boycott of the system leading to non-performance. Furthermore,
the system will lead to a collection of vast customer and
employee data. The privacy of the data may be a breach by the
cybercriminals who may sell the data to the organization’s
competitors or use it for other malicious activities. For instance,
they may use a customer’s financial information to defraud

them.
Risks of Not Doing the Project
Creative and innovative products and processes as a way of
reducing costs, increasing efficiency and attracting more clients
mar the current business environment. Therefore, not carrying
out the project means that the organization will be stagnant; it
will not be able to handle the changes in the business
environment. For example, the organization will not be to
gather and respond to the different customer concerns on time;
as such, the challenge reduces its competitive advantage and
loses its market share to competitors that adapt technology
(Lahovnik & Breznik 2014). Moreover, when the project is not
adopted, Phoenix Fine Electronics will have to invest heavily in
its expansion strategy, among the areas of investment that will
include marketing in the new markets. The high investment may
lead to losses in the youthful years of the new stores, unlike
when the system is used.
References
Lahovnik, M and Breznik, L (2014), Technological Innovation
Capabilities as a Source of Competitive Advantage: a Case
Study from the Home Appliance Industry. Transformations
in Business & Economics, Vol. 13, No 2 (32), pp. 144-160

Mehta, A (2016). BI, SCM, CRM, and ERP in a Nutshell and
their Relationship. Medium. Web. Accessed on 16/2/2020.
IT Business Partnership
IT Business Partnership
Katherine Askew
CMGT/5823
February 10, 2020
David Conway
Relationship between ERP, CRM, and DSS
Just like any other company, Phoenix Fine Electronics must
come up with ways of incorporating how they relate with their
customers, how they come about their decisions, and how the
enterprise functionalities affect the other two functions. To
achieve this aspect, there must be a relation between the three

concepts with a central focus on their Decision Support
Systems.
An article by Akhit Mehta suggests that the company must come
up with proper support systems that incorporate elements of the
system in use. For example, the company can focus on the
qualitative analysis of their business aspects to provide the
managers with the ability to make broader decisions on how the
system can support other aspects of the management. When it
comes to matters of Enterprise resource management, the
company will have to come up with integration modes of their
available functionalities to create a successful partnership
between the business and I.T sector. For example, the new CIO
will have to integrate various departments of the company such
as sales, manufacturing, human resource, and product planning
within the company to give the CEO a comprehensive report on
all the integration of activities.
On issues to do with the relationship between the company and
its customers, the CIO will have to look into new customer
preferences and compile a report which will show areas of the
company that needs work. The data likely to be collected will
focus on improving the company’s CRM system to provide the
customers with an active service delivery response that will be
beneficial to both the company and the customers. An additional
connection between the three functionalities, which are
enterprise resource management, customer relationship
management, and decision support system, will further be based
on how the company can maneuver the functions of the three
and still maintain an optimum level of profit maximization.

Executive Summary
Phoenix Fine Electronics will highly be influenced by the
decisions made by the CIO towards the set-up management
plans and needs. From a business expansion perspective, the
business will likely require the collaboration of the CFO and the
CIO in incorporating the functionalities of the discussed ERP,
DSS, and CRM. These functionalities are what stand to
highlight what business needs the company needs to work in
terms of expansion of branches and customer base. Some of the
desired outcomes from the integration of the three system
functionalities will vary with the seriousness and the level of
implementation.
The first likely desired outcome is that the business will want
to have a secure customer satisfaction scorecard to facilitate the
expansion of the new branches. This aspect will likely be
achieved through the joint success of the DSS and CRM. The
second possible desired outcome is that the business will
probably want to have a laid-out plan when it comes to the
expansion of the branches. In achieving this fete, the company
must have a planned-out system when it comes to the resources
available. This aspect will require thorough cooperation
between DSS and the ERM. The third desired outcome from the
business is that the CEO will likely want the company to realize
some profit or improvement in terms of the sales of the
products. This aspect will require the cooperation between DSS
and ERP in terms of coming up with laid out mechanisms that
will ensure that the production aspect of the business is updated
on the market demands.
It is only once the outcomes are met that the business will be
able to gauge the success of the functionalities of the three
processes in the company. The success of these processes is also
dependent on the flow of the functions as coordinated by the
DSS. Once the DSS comes up with proper means pf monitoring
these processes, then the company will likely achieve its desired
outcomes.

References
Mehta, Ankit. BI, SCM, CRM, and ERP in a Nutshell and their
Relationship. Medium
3 May 2016. Retrieved from https://medium.com/@metankit/bi-
scm-crm-and-erp-in-a-nutshell-and-their-relationship-
32630230cde9
Kolisnyk, Mariia. Relationship Between ERP and CRM. Diceus
3 Aug 2018. Retrieved from https://diceus.com/a-relationship-
between-erp-and-crm/
Business and IT Strategy
Katherine Askew
CMGT 583
February 3, 2020
David Conway

1
Overview
Identify the commonalities in the business strategy and IT
strategy.
List the critical elements of information technology needed.
Describe the importance of the critical elements.
Identify recommended changes to better align the two plans.
Describe the value added the business should realize if these
recommendations are adopted
Commonalities Between Business and IT Strategy
Both strategies aim at bringing about business value
They complement each other until the overall desired goals and
objectives are met.
They both require inputs in terms of resources such as capital.
An organization must set aside the resources
There are commonalities between business and IT strategies.
First, both aim at creating value for a business organization.

The goal is to realize the desired business value. Additionally,
the two need to complement each other. It means that they
should both produce results that are similar. Further, both the
strategies require inputs in terms of capital and other resources
(Yeganeh, 2019). These resources ensure that the set goal is
being realized. An organization must set aside resources that
will help drive both strategies.
3
Critical Elements of IT Required
To realize the strategy, there are critical elements of IT
required. First, human resources are required to draft and
implement the strategy. This entails skilled and competent IT
professionals. Also, an information technology system that
meets the business needs is required. It must ensure that the
information is centralized and secure from access by
unauthorized parties (Yeganeh, 2019). Reliable data sources are
required so that the IT system can help provide actionable
information to the organization. Reliable data will guide the
business decisions that are made.
4
Human resources are needed. Skilled and competent IT
professionals should be assigned the responsibility.
A new information technology system is required.
It must meet the business needs and ensure security of

information.
Reliable data sources are required. The data will be analyzed
and help guide business decisions.
The Importance of the Critical Elements
The resources are what the company needs to drive the business
goals.
An IT system requires human resources and credible data
sources for it to provide the desired outcomes.
If the company works on the two, it will attain better business
goals.
The critical elements outlined in the previous slide are very
important. First, they are primarily what the company needs so
that the desired goals can be realized. The IT strategy needs the
key resources which are human resources and credible data
sources. Mainly, an IT system will provide the best outcomes if
it can collect information from credible data sources. When
these two are worked on, the IT strategy will bring about the
desired business value.
5
The Recommended Changes
To better align the two plans, there are recommendations that
the company needs to consider. First, it should hire skilled and
competent IT professionals who will help draft and implement
the IT strategy. The IT team will work with other teams such as

marketers so that all teams can work on the same goal. Actually,
collective performance is deemed the most important approach.
All teams need to understand the goal that should be realized
and created synergy. This will create a new culture that will be
about pursuit for the targeted business goals.
6
The company needs to hire skilled and competent IT
professionals.
They will be required to draft and implement the strategy.
They will work with other teams such as marketers to ensure all
processes are aligned with the overall desired goal.
Continued….
It is important that a new culture is cultivated.
The culture is about aligning IT with business goals.
Motivation and performance evaluations will help realize the
new culture.
All teams should be motivated through rewards and provision of
all resources they might need.
Performance evaluation should be done to ensure process align
with the desired goals.
In addition to the creation of the teams, the management must
focus on cementing a new culture of aligning business and IT
goals. As such, motivation and performance evaluation need to
be undertaken. Motivation entails providing the teams with the
required resources and rewards whenever they realize certain

milestones (Thompson, 2017). Also, performance evaluation
should be routinely to achieve that the desired goals.
7
The Projected Value
Implementing the recommended changes will create value for
the organization. Information will be collected and analyzed
fast, hence help the organization make better decisions. The IT
system will enable the business to learn more about consumer
trends and preferences, thus align the supply chain with the
trends. Which will allow it to provide better services to the
customers. More so, the company will attain a better
understanding of the consumer markets and will implement
strategies that align with the market factors.
8
Implementation of the changes will create business value.
The company will gain a better understanding of the consumer
markets.
It will provide services and products that meet the needs.
A high customer satisfaction level will be realized.
The development will strengthen the company’s brand.

References
Thompson, J. (2017). Principles of Marketing. New York, NY:
Larsen and Keller Education .
Yeganeh, K. (2019). Major Business and Technology Trends
Shaping the Contemporary World (1st ed.). New York, NY:
Business Expert Press.
Read the following scenario and refer to it when you complete
the weekly assignments:
· Week 1: Business vs. IT Strategy Presentation
· Week 2: System Recommendation
· Week 3: Measurable Values
· Week 4: Strategic Sourcing Plan
· Week 5: SWOT Analysis
· Week 6: ROI Calculation and Business Case
Phoenix Fine Electronics (PFE) is a medium or mid-sized
company but growing rapidly each year selling technology
products to retail consumers. They have an annual revenue of
$15 million in sales. PFE started with one store but has grown
to 25 stores and has expanded into a second state.
PFE has one store in a town with a population of 100,000, and
three stores in towns with populations exceeding 200,000. The
goal of the company is to continue expansion into an additional
3 neighboring states within the next 5 years. PFE wants to
utilize the same population numbers to determine the number of
stores it should open. It would also like a marketing firm to do
an analysis of each town that meets the population criteria to
determine the best cites in which to open new stores.
Each store employs a store manager and an IT manager who
both directly report to the Chief Executive Officer (CEO).

The current IT plan for each store is to utilize technology to
support the store; increase sales; track inventory; secure store
customer data; perform payroll; and report all sales, inventory,
and payroll data to the main office. The IT manager is
responsible for managing the IT systems, making decisions on
what technology and software are needed, and implementing the
systems while ensuring accurate reporting to the main office.
The store manager is responsible for all staffing, inventory, and
sales functions within the store.
With expansion and the acquisition of smaller independent
stores, the CEO is worried about how department and customer
data can be aggregated to allow the company to make better,
timely business decisions. Even with such a wide footprint the
company must ensure unique, outstanding customer service and
provide value to the consumer base. The CEO lacks IT
experience and has been hesitant to adopt the suggestions of the
store and IT managers, which is to give the company an online
presence and advance the company into national competition
with other consumer electronics stores.
The CEO hired a Chief Financial Officer (CFO) and Chief
Information Officer/Chief Technology Officer (CIO/CTO). The
CFO will oversee the company finances for the expansion. The
CIO/CTO will oversee the consolidation of the disparate
systems and technologies that exist between the stores,
streamline the information gathering and reporting to the main
office, and develop an online presence that will catapult the
company into a competitive position on a national level.
Your job is to help the new CIO/CTO move PFE toward the
future.

Journal of Intelligent & Fuzzy Systems 35 (2018) 2827–2836
DOI:10.3233/JIFS-169636
IOS Press
2827
Research on the collective efficacy of social
networks with multi factor analysis
Peng Fan∗
Business School, Central South University, Changsha, China
Abstract. With the rapid development of Internet technology,
social networks have been widely used in the world, and some
of them are really active and some people are just browsing.
Based on this, the collective efficacy was proposed and the
three
element interaction determinism was studied. The similarity
between social network users was calculated and integrated, and
the collective efficacy was studied. 60 members of the four
network groups were interviewed, and 15 influencing factors of
network group efficacy were coded. 230 college students were
investigated by questionnaire and the multi factor analysis
method was integrated. The influence of community members’
efficacy on their community involvement was studied through
the initiative, focusing on sharing information and other
dependent variables, attitudes, interests, values, personality and
other
independent variables. The research results showed that
increased awareness of the degree of interpersonal similarity
will
increase the degree of involvement of social network group
members, and psychological involvement played an
intermediary
role in perceived interpersonal similarity and the increases of

perceived interpersonal similarity will enhance the formation
of the sense of group efficacy.
Keywords: Multi factor analysis, social network, collective
efficacy
1. Introduction
The emergence and popularity of the Internet has
brought great changes to people’s life. The social net-
work with a wide variety of functions has become
an integral part of the life style and daily life of
the majority of Internet users gradually. Micro-blog,
social networking sites and other social networks
have become the third major Internet applications
of instant messaging and online banking. Social net-
work transferred the right to master the resources to
the majority of Internet users. The interaction of the
website and the user, the participation of the users,
the integration of the resources and the externality
of the network achieved a huge leap [1] It can be
seen throughout the social networking market that
micro-blog Sina, QQ space, all networks, the world
∗ Corresponding author. Peng Fan, Business School, Central
South University, Changsha, China. E-mail: fanpeng2011
@outlook.com.
community, campus BBS and other social network
operators were very successful and achieved good
performance [2].
The successful operation of social networks
depended on the understanding of the needs and
preferences of the community members in the vir-
tual community. It was necessary to know that what

factors allow community members to use the com-
munity and stay in the social network for a long
time. That is to say, what are the factors that enhance
the cohesion of social networks and how to enhance
the community’s collective efficacy, which was very
important for the development of social networks [3].
Social network was a new life style of human beings.
Members of a social network can communicate and
participate in community related activities for a long
time. Social network generated attraction and affin-
ity to community members and the intimacy as well
as affinity between members have deepened grad-
ually [4]. Thus it can be seen that social networks
included many characteristics including cohesion
1064-1246/18/$35.00 © 2018 – IOS Press and the authors. All
rights reserved
mailto:fanpeng2011penalty [email protected] @outlook.com
2828 P. Fan / Research on the collective efficacy of social
networks
among the members in the traditional community
[5]. The production of social network cohesion was
inevitable and it was the inevitable result of the devel-
opment of interpersonal relationships [6]. The level of
social network cohesion had an important impact on
the collective efficacy of social networks to the social
network service, so it is very important to under-
stand and study the cohesion and collective efficacy
of social networks [7].
There were users who used big V in micro-blog
detonated traffic and integrated its own fan base,

which let customers repast from the community to
the line of the line to the real store dining from the
online community to the physical stores line down
[8]. Finding the catalyzer of members of the network
community involved in the psychological involve-
ment of the community into the behavior of the
community will be a way of marketing for social
economic times [9]. With the enhancement of the
network self-efficacy, people’s attitude towards the
corresponding network subject will be increased,
which made people can’t help but think of Bandura
will be extended to the level of self-efficacy of a con-
cept - group efficacy. Whether it can play a role in the
process of community members involved in the net-
work community. What factors can contribute to the
formation of group efficacy of network community
members [10].
2. Collective efficacy
2.1. Three element interaction determinism
Psychologists had to answer what determined the
human mind and behavior in the creation of the the-
ory. Bandura has made three-yuan-decide answer and
its unique lied that he put the person’s subjective fac-
tors into the psychological and behavioral function of
the causal decision model. The three element interac-
tion determinism hypothesized that the environment,
the internal factors and the behavior of the three fac-
tors were independent of each other, and they were
interactive with interactive decision [11]. The inter-
active decision model of the three was shown in the
following figure:
B, P, E represented the behavior, the main body and

the environment respectively, and the two-way arrow
indicated that the relationship between the two fac-
tors was interactive in the graph. Both the model and
the intensity of the model changed with the change
of B, P and E. For example, E, as the object and
Fig. 1. Bandura’s reciprocal determinism.
the external conditions of the B part, determined the
mode and intensity of B, and B can also change the
E so that it can adapt to the needs of people. P and B
were also determined by each other. The internal fac-
tors such as motivation, intention, goal, emotion and
so on affected the behavior pattern and intensity of P,
in the same way, the internal characteristics and exter-
nal results of B affected or partially determined the
P’s intention to beliefs and emotional responses [12].
In the relationship between P and E, although per-
sonal characteristics, emotional and cognitive ability
of P were the product of the specific environment
and subject to the constraints of environmental con-
ditions, on the other hand, E also depended on the
cognitive grasp of P. E can affect P only when it was
grasped by P.
2.2. The concept and nature of collective efficacy
Bandura defined collective efficacy as: “a common
belief in the ability of team members to combine their
teams to achieve a certain level of performance in a
situation”, which was the definition that was accepted
by most researchers commonly. Collective efficacy
was defined as a collective belief in the success of
a specific task, which reflected the expectation of a
group to accomplish a specific task. Collective effi-
cacy referred to the ability of the members to perceive

and evaluate the ability of the group, not the ability
of the group itself.
Collective efficacy strength of individuals with dif-
ferent status or role was different in the collective. At
the same time, collective efficacy also changed with
the field of collective activities. The collective may
appear to be very confident in an activity, but the col-
lective perception of the efficacy of the belief was
very low in another area. Thus, collective efficacy
was not a static group feature, which was fluctuating
P. Fan / Research on the collective efficacy of social networks
2829
with the constant change of the relationship between
the members and the external pressure of the exter-
nal reality. However, as a collective property, we
can use the consistency within the group rather than
the differences among groups as the main indicators
of the common beliefs of the group [13]. Bandura
believed that the factors affecting self-efficacy, such
as acquired experience, social persuasion and so on
will also affect the collective efficacy in a wide sense.
In Bandura’s view, collective efficacy beliefs can
predict the level of group behavior. The study and
regulation of collective efficacy of groups can predict
and control the behavior of these groups.
3. Social networking collective efficacy
3.1. Social network user relations
A social network was the network service that

user can establish an open or semi open account and
each other connected through the link. Social net-
works in China have become Web2.0 business with
the most extensive coverage of users, the most influ-
ential spread of and the highest commercial value
[14].
The complex and special relationship among the
users in the social network can be studied by the
social network. The formation of social network was
based on the form of user network. Different users
were different nodes in the network, and you can use
G (V, E, W ) to express a social network, V was a
collection of users, E represented the edge of the col-
lection. If two users Vi and Vj had a relationship, there
was a side e(Vi, Vj ), and W represented the weight.
Fig. 2. Design the network.
The weight of the size can be different set according
to the need [15].
There were three different forms of social net-
working data according to the current situation of the
development of social networks. The first was the two
friends confirm the relationship and this kind of net-
work friends need mutual recognition. Otherwise it
can’t successfully to set up friend relationship, which
was represented by Facebook, all networks and so
on. The second category was one way concern type.
Users concerned about other users and did not need
each other must pay attention to their own, which
can be chosen according to their own interests and
was represented by the Twitter, micro-blog and Sina.
The Third types were community groups. There was
no clear relationship between the user, but the same

community had some similar characteristics [16].
Traditional personalized recommendation method
assumed that users were independent and identically
distributed, and it ignored the trust between users
based on social relations and the collective efficacy.
3.2. Current situation of social network and the
similarity between users
The data showed that China’s total population was
nearly 1 billion 340 million and the proportion of
urban and rural population counted 50 percent in the
statistics on Chinese Internet users. Internet users
were 485 million and the Internet penetration rate
reached 36%. Nearly 920 million were mobile phone
users and mobile phone penetration rate was 67%.
Chinese Internet users believed that the Internet was
the most attractive media, which was more than TV.
Chinese Internet users spent 41% of the time on
Fig. 3. Chinese Internet users and the present situation of social
networks.
networks
Fig. 4. Social networking activities, items to promote collective
efficacy.
social networking, and 77% of Chinese Internet users
believed that the brand will be more attractive to par-
ticipate in social networking.
The similarity between users can be reflected by

their strong association operation and weak corre-
lation operation. The strong correlation operation
referred to the direct interaction between the users,
such as forwarding, comments, sharing and other
operations. Weak correlation operation referred to
the user was not obvious interaction between rela-
tions, such as attention to the same common page,
which often reached the same geographic location
or common used of the same site applications and
so on. And the formula Sim (s, v) = asvn∑
k−1
ask+1
· h1 +
bsv
n∑
k−1
bsk+1
· h2 + csvn∑
k−1
csk+1
.h3 was used to calculate the
similarity of two users. Among them, represented
user v and user s similarity, and a(s, v) represented
user v comments on the number of user s. bsv indi-
cated the number of times the user v to the user s,
and csv represented the share number of user v to
users s. A, B, C, respectively, to comment, forward,
share the rights of these 3 operations. A, B, C, respec-
tively, to comment, forward, share the rights of these

3 operations. h1, h2, h3 represented respectively the
rights of comment, forward, and share. Usually the
similarity was proportional to the collective efficacy.
3.3. Recommendations based on group efficacy
Group performance recommendation behavior
was a group of two or more than two groups of users to
initiate projects and to recommend. For example, the
Fig. 5. Aggregation method of individual results.
originator of a social network launched an activity,
such as the launch of tourism activities, the pur-
chase of products or services and so on. Collective
efficacy produced influence to willingness or behav-
ior of participate in other group members. Group
recommendation was based on the individual rec-
ommendation, but it was not a simple addition of
individual recommendation [17].
It can be used to study the collective efficacy
of social networks through the establishment of the
aggregated individual model. The main idea of this
method was to aggregate the individual model into
a group model, then it was suitable for the group
and it was easy to produce the model of collective
efficacy. However, the combination mode of this sin-
gle may produce a reasonable group recommendation
2831
Fig. 6. Aggregating groups model method.

because each user group may be preferred to different,
which twisted group user preference profile, thereby
reduced the degree of satisfaction with the group of
users for the recommended results and can’t play the
effect of group efficacy.
When studying the group recommendation system,
regardless of any of the two strategies men-
tioned above, appropriate aggregation strategies are
required. Different aggregation strategies can be
applied to different scenarios, depending on the
system and group requirements.
Computational social similarity:
S ∈ Rnxn is used to show the user’s social network,
and n is the number of users. If the user U is concerned
about the user V , then Suv = 1, otherwise Suv = o,.
For the relationship matrix S ∈ Rnxn, the propagation
attenuation coefficient is β. The propagation attenu-
ation coefficient is the closeness between the users,
and the attenuation ratio of each layer is increased.
Assuming that the information of the user U needs
g(u, v) times to be sent to the user V , and the user’s
new social relationship matrix K can be expressed as:
Suv = βg(u, v) • U(g(u, v) − k) (1)
In formula (1) U(x), when x ≤ 0, U(x) = 1; when
x > 0, U(x) = 0. After obtaining new social relation
matrix of users through the formula (1), we can use
cosine similarity to calculate the social similarity of
user U and use V , and the formula is as follows.
Simsocial(u,v) =

⇀
u · ⇀v
|⇀u||⇀v|
· (2)
Fusion social network similarity:
The Pearson coefficient is used to calculate the sim-
ilarity between the two users, which can be expressed
as follows.
Simrating(u, v) =
∑
i∈I (rui−r̄ )(rvi−̄r)√∑
ieI
(rui−r̄ )2
∑
iel(rvi−r̄ )2
(3)
In formula (3), Simrating(u, v) is the score similar-
ity of user U and V , rui is the score of user U for the
item I, and r̄ u is the average value of the item scores
by user U. The simplest linear relationship can be
used to fusion score similarity and social similarity.
Sim(u, v) = α · Simrating(u, v) + (1 − α) ·
Simsocial(u, v) (4)
Whereas, 0 ≤ α ≤ 1. When α < 0.5, the social
similarity plays a major role. When α > 0.5, the score
similarity plays a major role. And when α = 0.5, the

degree of similarity is equal to the social similarity.
Integration of social networks and social similarity
score similarity is made, and the fused similarity is
applied in the group recommendation system based
on collective, so as to improve the quality of group
recommendation system, and enhance the sense of
collective efficacy.
4. Study on the influencing factors of the
group efficacy
4.1. The actual influence factors of the group
efficacy
In reality, there are many factors that affect the
efficacy of the group, which are summarized in the
following. The first is the past achievements. The
school’s average academic achievement is an effec-
tive predictor of teacher group efficacy. The second
is the sense of self-efficacy. Self-efficacy is an effec-
tive predictor of group efficacy. The third is the key
member. Group members often take into account the
performance of key members of the group when they
judge the effectiveness of the group. The fourth is the
task scenario. Group interdependence may be another
important predictor of group efficacy. But the com-
munity in the real situation is very different with the
network community. For example, the network com-
munity can create different mechanisms for collective
action, collective action network including the rela-
tive indirect behaviors such as browsing information
about local problems, and some direct actions such as

networks
government officials contacted by mail [18]. There-
fore, these factors have also changed. In this research,
the interview method was used to get the text that
affects the network group efficacy, and then a series
of analysis was carried on in order to explore the new
influence factors in the network context.
4.2. Research design
As an exploratory research, the interview method
was mainly used in this part to explore the influence
factors of the network group efficacy. In this study, 60
members from four Internet groups were selected and
interviewed. Each group had 10 members to accept
the network interview, and in order to eliminate the
interference of gender factors, especially 5 male and 5
female were selected. The whole process of the inter-
view was recorded. After the interview, the recording
data were collected under the guidance of experts, and
the text information was extracted according to the
root theory to analyze the data from the beginning to
the end. After many discussions, the influence factors
of the network group efficacy were summarized.
4.3. Structured interviews
The network groups for the structured interview
include: flash mob; game teams in online games;
group tour pal; some members of the tour pal group
launched in micro-blog. Interview questions are as
follows.
(1) The basic information of population statistics
(gender, age, education, etc.)

(2) Are you in a network group with clear group
goals? What is the name or type of the group?
The number of members in a group? Group
time and the time you join (for example, A:
less than 6 months, B: 6∼12 months, C: 1∼2
years, D: 2 years or more)
(3) Would you please briefly describe the group
goals of an action or task in your network
group? Think about your current group, and
select the appropriate number based on your
feelings. (1 - not very agree; 2 - not consent;
3-disagree a little uncertain; 4- uncertainty; 5 -
somewhat agree; 6- consent; 7 - quite agree)
Group efficacy: I believe that my group will be
able to do a good job. (1–7 points); By work-
ing hard, I am can complete the arduous task
in the group. (1–7 points); I believe that my
group can effectively deal with the problem of
sudden. (1–7 points); My group has the ability
to complete the task. (1–7 points).
(4) Please specify the reason you feel in the prob-
lem (3) (influence factors)
In order to guarantee the reliability of the open
coding, the materials obtained from the interviews
are coded and sorted out by the two codes. If there
is inconsistent with the situation, they can discuss in
accordance with the literature and related research.
If it still cannot be resolved, the relevant experts will
give advice. In the end, the primary encoding library
with 15 entries is obtained.

A1: The perception of the characteristics of the
promoter; A2: Perception of self-ability; A3: Cooper-
ation with the members of the situation; A4: Member
relationship closeness; A5: Leader’s personal ability;
A6: The ability of a good team player; A7: Com-
munication with others; A8: Similar identities and
experiences; A9: The situation in the past; A10: Rela-
tionship with other members; A11: The number of
people involved; A12: Difficulty level of perceived
task; A13: The perception of others and their own
similar situation; A14: The time of group existence;
A15: Judgment of team hardware condition.
In order to obtain the accurate and effective conver-
gence model, 14 graduate students were found from
the Business College of Tsinghua University, and
they were randomly divided into two groups for the
interview on issue. For example: members of the first
group reached a consensus, that was, the “leader’s
personal ability” and “outstanding members of the
ability” was summarized as “key members”. Accord-
ing to induction results of the two groups and experts’
guidance, the factors that affected the efficiency
of network group were obtained finally, namely:
past achievements; key members; self-efficacy; group
properties (including interdependence scale, pop-
ulation etc.); task; participate in communication;
perceived similarity [19].
4.4. Research results
Combined with the literature review and research
results, it is not difficult to find that the factors men-
tioned above have been studied and verified in the
previous several factors. The degree of participation

in communication and perceived similarity are the
unique factors in the network context. It is because of
the changes in the field that makes the two new factors
also contribute to the formation of group efficacy. In
order to ensure the quality of reliability and validity,
2833
reliability test found some graduate and PhD who did
not participate in the encoding to encode the text, and
it was found the encoding similarity was 80%, so as
to ensure the credibility of qualitative research.
5. Collective efficacy of social network based
on multi factor analysis
5.1. Research assumptions
Interpersonal similarity can be defined as a lot of
different dimensions. The operation of homogeneity
(a term that means “the same hobby”, and sometimes
with the perception of similarity) includes two dimen-
sions, the background and the homogeneity of the
attitude. In general, the homogeneity or the similarity
of the attitude is more predictive than the evaluation
of the source by homogeneity of the demographic
characteristics [20]. However, social proximity (such
as demographic data) can predict the similarity in
another area (such as attitude) in a certain area. For
this reason, the perception of similarity has a more
significant predictive effect than that of the actual
or objective similarity. The concept of interpersonal
similarity actually used the way of expression of the

attitude similarity, but it illustrated the potential com-
monality, which was not only the attitude, or enduring
belief. The following assumptions were put forward.
H1: Perceived interpersonal similarity of members
of the network community has a significant positive
effect on their behavior.
H2: Perceived interpersonal similarity among
members of the network community plays a role in
the psychological involvement and behavior of the
community.
H3: The perceived similarity of the members of the
network community has a significant positive effect
on the formation of the group efficacy.
H4: The community members’ sense of com-
munity efficacy plays a regulatory role in the
psychological involvement and behavior of the mem-
bers of the community.
5.2. Research design
The multi factor analysis method was fused in
this study to find the measurement of each vari-
able, and the dependent variable was the behavior
involved. The corresponding independent variable
was perceived interpersonal similarity. The depen-
dent variables were initiative and focusing on sharing
information, and the corresponding independent
variables were attitude, values and personality char-
acteristics. Using the 7 point scale as the tool, after
the adaptation, the pre-test and the re adaptation, the
formal questionnaire was obtained. The subjects were

230 students from different schools. Questionnaires
were distributed and recovered, and 160 valid ques-
tionnaires were obtained. Among them, 78 were male
and 82 were female. In order to ensure the credibility
of the answer, participants used the anonymous way
to answer questions.
5.3. Data analysis
We first used SPSS 20.0 to measure the various
dimensions of the item for the exploratory factor anal-
ysis, and calculated the weighted average number.
Then the mean and variance analysis and Pearson
correlation test were carried out on each dimension
of each variable, and the correlation between the vari-
ables was found to be more significant. The specific
situation is shown in Table 3. Among them, the corre-
lation of perceived similarity, behavioral involvement
and psychological involvement was higher than 0.29,
which fully explained the mediating role of psycho-
logical involvement in the two.
In order to verify the hypothesis of H1, a linear
regression analysis of perceptual similarity to behav-
ior involvement was made in this paper. It was found
that the correlation between the various dimensions
was significant, and it was positively correlated with
each other. The specific situation is shown in Table 2.
In order to verify the hypothesis H2, the results
of an intermediary analysis are shown in Table 3.
Because each variable had two or more dimensions,
one of them was only one example. In general,
psychological involvement played the intermediary
role partly in mediating the relationship between
perceived interpersonal similarity and behavioral

involvement.
The same as hypothesis H1, hypothesis H3 was
also a regression analysis of the causal relationship.
Finally, it was found that the causal relationship
between perceived interpersonal similarity and group
efficacy was significant. Hypothesis H4 tested the
moderating effect of group efficacy on psychologi-
cal involvement and behavior involvement. We also
took a dimension as an example, and made the data
as in Table 4. It was found that the group efficacy
only played a moderating role in the psychologi-
cal involvement and the sharing of the information
dimension.
networks
Table 1
Statistical properties of each variable and its correlation
coefficient
mean standard attitude values personality attribution associated
Initiative Share collective
value deviation information efficacy
attitude 5.44 1.153 1
values 5.35 1.235 0.727∗ ∗ 1
personality 4.81 1.275 0.587∗ ∗ 0.609∗ ∗ 1
attribution 5.08 1.331 0.534∗ ∗ 0.541∗ ∗ 0.431∗ ∗ 1
associated 4.94 1.311 0.522∗ ∗ 0.456∗ ∗ 0.444∗ ∗ 0.835∗ ∗ 1
Initiative 5.24 1.310 0.522∗ ∗ 0.415∗ ∗ 0.290∗ ∗ 0.688∗ ∗
0.686∗ ∗ 1
Share information 5.33 1.381 0.493∗ ∗ 0.474∗ ∗ 0.271∗ ∗

0.755∗ ∗ 0.689∗ ∗ 0.794∗ ∗ 1
collective efficacy 4.97 1.203 0.499∗ ∗ 0.521∗ ∗ 0.427∗ ∗
0.806∗ ∗ 0.778∗ ∗ 0.739∗ ∗ 0.770∗ ∗ 1
Table 2
Regression analysis of perceived interpersonal similarity on
behavior
Dependent independent Non standardized value Coefficient R2
adjustment F
variable variable coefficient significance R2
Behavior involvement Perceived interpersonal similarity
Perceived interpersonal attitude 0.593 7.692 0.006 0.272 0.268
59.159∗ ∗ ∗
similarity Sense of worth 0.440 6.835 0.003 0.172 0.167
32.834∗ ∗ ∗
personality characteristics 0.299 3.815 0.000 0.084 0.079
14.553∗ ∗ ∗
Focus on sharing information attitude 0.590 7.119 0.000 0.243
0.238 50.684∗ ∗ ∗
Sense of worth 0.530 6.759 0.000 0.224 0.219 45.691∗ ∗ ∗
personality characteristics 0.294 3.542 0.001 0.074 0.068
12.544∗ ∗ ∗
Table 3
Regression analysis of psychological involvement in perceived
interpersonal similarity and behavioral involvement (for
example)
Model Model 1 Initiative Model 2 Initiative Model 3 Initiative
Coef. T sig. Coef. T sig. Coef. T sig.
attitude 0.593 7.692 0.006 0.246 3.263 0.001

Sense of belonging 0.667 11.922 0.000 0.564 8.643 0.000
R2 0.272 0.474 0.507
Table 4
Regression Analysis of group efficacy (for example)
Model Model 1 Model 2 Model 3
Focus on sharing Focus on sharing Focus on sharing
information …
Age Differences in Reported Social Networks and Well-Being
Wändi Bruine de Bruin
University of Leeds and Carnegie Mellon University
Andrew M. Parker
RAND Corporation, Pittsburgh, Pennsylvania
JoNell Strough
West Virginia University
Social networks can consist of close friends, family members,
and neighbors as well as peripheral others.
Studies of social networks and associations with well-being
have mostly focused on age-restricted
samples of older adults or specific geographic areas, thus
limiting their generalizability. We analyzed 2
online surveys conducted with RAND’s American Life Panel, a
national adult life span sample recruited
through multiple probability-based approaches. In Survey 1, 496
participants assessed the sizes of their
social networks, including the number of close friends, family
members, neighbors, and peripheral others.

Of those, 287 rated their social satisfaction and well-being on
Survey 2. Older participants reported
smaller social networks, largely because of reporting fewer
peripheral others. Yet older age was
associated with better well-being. Although the reported number
of close friends was unrelated to age,
it was the main driver of well-being across the life span— even
after accounting for the number of family
members, neighbors, and peripheral others. However, well-
being was more strongly related to social
satisfaction than to the reported number of close friends—
suggesting that it is the perception of
relationship quality rather than the perception of relationship
quantity that is relevant to reporting better
well-being. We discuss implications for social network
interventions that aim to promote well-being.
Keywords: life span, social network size, friendship, social
satisfaction, well-being
Supplemental materials:
http://dx.doi.org/10.1037/pag0000415.supp
Social networks can consist of different types of social contacts,
including close friends, family members, and neighbors as well
as
peripheral others (Wrzus, Hänel, Wagner, & Neyer, 2013). The
Convoy Model posits that older individuals will be followed by
fewer fellow travelers on the road of life (Antonucci, Ajrouch,
&
Birditt, 2014). Whereas the core of close contacts may remain
stable with age, the number of superficial contacts in the
periphery
of the convoy are expected to decrease as a result of personal
and

situational factors, including health and income (Antonucci et
al.,
2014). Socioemotional Selectivity Theory (Carstensen, 2006)
has
been incorporated into the Convoy Model (Antonucci et al.,
2014)
and posits that older adults may deliberately limit their social
relationships to emotionally close social partners so as to
benefit
their well-being. Thus, this combined conceptual framework
pre-
dicts that overall social network size will decrease with age
with-
out reducing emotionally close relationships that are relevant to
well-being. Here we present secondary analyses of data
collected
with a national adult life span sample to examine age
differences
in reported social network size, including the number of close
friends, as well as associations with social satisfaction and
well-
being across the life span—while accounting for age differences
in
health, income, and other demographic factors. We first review
the
existing literature on these topics.
Age Differences in Social Network Size
A 2012 review of 277 studies of social network size found that,
across longitudinal and cross-sectional designs, reported social
network sizes decreased with increasing adult age (Wrzus et al.,
2013). Most of the reviewed studies were carried out among
older
adults (over age 60 years) or younger adults (under age 45
years)

rather than among middle-aged adults (aged 45– 60 years), with
This article was published Online First November 7, 2019.
X Wändi Bruine de Bruin, Centre for Decision Research, Leeds
Uni-
versity Business School, University of Leeds, and Department
of Engi-
neering and Public Policy, Carnegie Mellon University; Andrew
M. Parker,
RAND Corporation, Pittsburgh, Pennsylvania; JoNell Strough,
Department
of Psychology, West Virginia University.
Data collection and Andrew M. Parker were supported by the
U.S.
National Cancer Institute (R21CA157571) and the U.S. National
Institute
of Allergies and Infectious Diseases (R01AI118705). Wändi
Bruine de
Bruin was additionally supported by the Swedish Foundation for
the
Humanities and Social Sciences (Riksbanken Jubileumsfond)
Program on
Science and Proven Experience and the National Institute on
Aging
(P30AG024962). These funders had no role in study design,
data collec-
tion, data analysis and interpretation, writing the report, or the
decision to
submit the report for publication. No financial disclosures were
reported by
the authors of this paper.
We thank Tania Gutsche for encouraging us to write this paper
and

David Grant and Julie Newell for their assistance in regard to
RAND’s
American Life Panel.
Correspondence concerning this article should be addressed to
Wändi
Bruine de Bruin, Centre for Decision Research, Leeds
University Business
School, University of Leeds, Maurice Keyworth Building, Leeds
LS2 9JT,
United Kingdom. E-mail: [email protected]
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Psychology and Aging
© 2019 American Psychological Association 2020, Vol. 35, No.
2, 159 –168
ISSN: 0882-7974 http://dx.doi.org/10.1037/pag0000415
159
https://orcid.org/0000-0002-1601-789X
mailto:[email protected]
http://dx.doi.org/10.1037/pag0000415
studies of younger adults having relatively small sample sizes
(Wrzus et al., 2013). Initial studies that did recruit large

national
samples tended to focus on age-restricted samples of older
adults
aged 50� years, and showed limited or no age differences in
social
network sizes (Antonucci & Akiyama, 1987; van Tilburg, 1998).
The one national adult life span study on age differences in
social
network size that we did uncover is from 30 years ago (Morgan,
1988), which predates online social networking sites. It found
that
reported social network size was negatively associated with
older
adult age, independent of potential age differences in health,
income, and demographic factors (Morgan, 1988). This general
pattern supports predictions from the Convoy Model (Antonucci
et
al., 2014) and Socioemotional Selectivity Theory (Carstensen,
2006). However, the study could not provide insights about
whether more emotionally close relationships were maintained
with age because of lacking the relevant measures.
More recent studies about age differences in online rather than
offline social networks did provide such insights (Chang, Choi,
Bazarova, & Löckenhoff, 2015; Yu, Ellison, & Lampe, 2018).
Older adult age was associated with reporting fewer Facebook
friends (Chang et al., 2015), even when considering only an
age-restricted sample of Facebook users aged 50 years and older
(Yu et al., 2018). These findings held when accounting for
health,
income, and demographics (Chang et al., 2015; Yu et al., 2018),
thus again suggesting that age differences in these factors may
not
account for older adults’ smaller social networks. Perhaps more
importantly, these studies were able to observe that older adult
age

was associated with reporting a greater proportion of actual
friends
among Facebook friends (Chang et al., 2015; Yu et al., 2018),
with
actual friends reflecting individuals with whom the user had a
relatively stronger and offline connection (Ellison, Steinfield, &
Lampe, 2007).
The Importance of Close Friends for Social
Satisfaction and Well-Being
Generally, it has been found that well-being is at least as good
or better for older adults relative to younger adults (Carstensen
et
al., 2011; Carstensen, Pasupathi, Mayr, & Nesselroade, 2000;
Charles, Reynolds, & Gatz, 2001; Kessler & Staudinger, 2009).
Thus, age-related declines in social network size do not appear
to
undermine well-being in later life.
The conceptual framework provided by the Convoy Model
(Antonucci et al., 2014) and Socioemotional Selectivity Theory
(Carstensen, 2006) posits that older adults have smaller but
more
emotionally meaningful social networks. Most evidence for
these
predictions comes from studies with age-restricted samples of
older adults. For example, an early study of Berlin residents
aged
70� years found that feelings of social satisfaction (a
component
of overall life satisfaction; Pavot & Diener, 2008) showed
stronger
correlations to reporting a greater absolute number of
emotionally
close contacts than to overall social network size (Lang &

Carstensen,
1994). Life satisfaction was also more strongly associated with
the reported number of friendship ties than with the reported
number of family relationships, in a study of the local commu-
nity networks of Iowans aged 50 –98 years (Goudy & Goudeau,
1982). Among U.S. residents aged 65 years and older,
friendship-centered social networks were associated with better
well-being than family-centered social networks (Litwin &
Shiovitz-Ezra, 2011). Similar findings were reported for Israelis
aged 60 years and older, such that individuals with neighbor-
centered networks fell in between individuals with friendship-
centered or family-centered networks in terms of their reported
morale (Litwin, 2001).
Two studies did examine age differences in social network size
and associations with well-being across the adult life span but
used
otherwise restricted samples. In the first study, participants
were
recruited only from communities in the San Francisco Bay area
(Fung, Carstensen, & Lang, 2001). Social network size was
found
to be greatest in young adulthood, with older adults reporting
lower absolute numbers of peripheral others— but the reported
absolute number of close social partners was similar across age
groups (Fung et al., 2001). Yet reporting a greater percentage of
close social partners in the social network was related to lower
levels of reported happiness in younger adults and unrelated to
reported happiness in older adults (Fung et al., 2001). In a more
recent follow-up study with the same sample, longitudinal
analyses
also found that older age was associated with smaller overall
social
network size and unrelated to the reported absolute number of
social contacts in the inner circle (English & Carstensen, 2014).

In
an additional cross-sectional analysis, older age was associated
with reporting less negative emotion and more positive emotion
about social relationships as well as reporting greater well-
being—
but the number of close relationships played no role, and there
were no age differences in the contribution of close
relationships to
well-being (English et al., 2014).
However, residents of San Francisco County and California are
not necessarily representative of the U.S. population because of
having much higher median household income ($96,000 and
$67,000 respectively, vs. $57,000 in the United States) and
much
more population per square mile (17,179 and 239.1,
respectively,
vs. 87.4 in the United States; United States Census Bureau,
2019).
In addition to better access to public transportation, these
factors
may contribute to why older San Franciscans are able to meet
up
with their friends more often than older adults in, for example,
San
Antonio, Texas (Carp, 1980, 1988).
The second study that examined age differences in social net-
work size and well-being focused specifically on the online
social
networks of U.S. Facebook users (Chang et al., 2015). Those
who
were older (vs. younger) reported having a smaller absolute
num-
ber of actual friends and overall friends on Facebook as well as
a

greater proportion of actual friends among their Facebook
friends
(Chang et al., 2015). Of these social network measures, only the
proportion of actual friends among Facebook friends was corre-
lated to better well-being (Chang et al., 2015). This relationship
did not vary by age, suggesting that the proportion of actual
friends
among Facebook friends was important for well-being across
the
life span (Chang et al., 2015).
Although prior research recruited Facebook users through ran-
dom digit dialing, one limitation is that Facebook users are not
representative of the general population. In 2019, only 46% of
adults aged 65� years reported using Facebook, as compared
with
79% of adults aged 18 –29 years (Pew Research Center, 2019).
Moreover, in two studies of older adults, conducted among
Geor-
gia residents aged 65� years (Hutto et al., 2015) and U.S. resi-
dents aged 50� years (Yu et al., 2018), relatively older users of
online social networking sites were found to be especially
different
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160 BRUINE DE BRUIN, PARKER, AND STROUGH

from same-age nonusers in terms of reporting feelings of greater
social connectedness.
Thus, we found no research with a national life span sample that
examined both age differences in social network size and
compo-
sition as well as its association with social satisfaction and
well-
being. Such data are needed to test predictions from the Convoy
Model (Antonucci et al., 2014) and Socioemotional Selectivity
Theory (Carstensen, 2006) about older adults having smaller
social
networks of more emotionally close contacts that benefit well-
being.
The Importance of Social Satisfaction for Well-Being
Close relationships may promote well-being when they are a
source of social satisfaction and social support, but they can
also
undermine well-being when they are emotionally draining and
causing relational stress (Birditt et al., 2018; Hartup & Stevens,
1999). A meta-analysis of 286 studies with only older adult
sam-
ples suggested that, for well-being in later life, the perceived
quality of social interactions was more important than the
reported
social network sizes (Pinquart & Sörensen, 2000). Subsequent
studies with older adult samples have shown similar patterns.
For
example, in a sample of Americans aged 57– 85 years, the per-
ceived quality of social contacts was more important than actual
number of social contacts for promoting feelings of well-being

(Cornwell & Waite, 2009). In a national adult life span sample
of
American adults aged 60 years and older, the association
between
reporting relatively frequent interactions with friends and less
depressive symptomatology was reduced after considering the
association between perceived quality of social contacts and
less
depressive symptomatology (Fiori, Antonucci, & Cortina,
2006).
Among African Americans aged 55 years or older, perceived
aspects of family and friend support networks such as reported
closeness and negative interactions were more important than
structural aspects of the social network (Nguyen, Chatters,
Taylor,
& Mouzon, 2016). In a sample of Los Angeles residents aged
60�
years, the number of close social contacts was less strongly
asso-
ciated with depressive symptoms and fatigue than was were
their
reports of feelings about their social contacts (Cho et al., 2018).
In
the one study that recruited a life span sample of San Francisco
Bay Area residents, also referred to above, older age was
associ-
ated with reporting more positive and less negative emotions
about
social networks, which, in turn, predicted well-being, whereas
social network size did not (English et al., 2014). However,
none
of these studies included a nationally representative life span
sample.
The Current Study

In a national adult life span sample, we examined the relation-
ship between age and the size of social networks (including the
number of close friends, family members, neighbors, and
periph-
eral contacts from other social groups) as well as the
importance of
the number of close friends and social satisfaction for well-
being
across the life span. Our paper adds to the literature reviewed
above, which, as noted, has tended to test predictions derived
from
the Convoy Model (Antonucci et al., 2014) and Socioemotional
Selectivity Theory (Carstensen, 2006) in samples that were age
restricted, geographically restricted, or focused on Facebook
users
only. The only study on age differences in social network size
referred to above that did use a national life span sample of
community-dwelling adults predates online social networking
sites
and could not test predictions about age differences in close
relationships or associations with well-being or social
satisfaction
because of a lack of such measures (Morgan, 1988).
Here we therefore report secondary analyses of national surveys
conducted with RAND’s American Life Panel in 2011–2013, to
test the following hypotheses:
1. (a) Reported social network size decreases with age, but
(b) the reported number of close friends does not.
2. Older age is associated with greater (a) social satisfaction
and (b) well-being.
3. Reporting more close friends is related to greater (a)

social satisfaction and (b) well-being, especially in older
age.
4. Well-being is associated with the reported number of
close friends and social satisfaction, with the latter being
a stronger predictor.
Method
Our secondary analysis used data from two online surveys that
were independently launched by two separate research teams for
different research purposes.1 We analyzed age differences in
social
networks assessed in Survey 1 (Hypothesis 1) as well as their
relationships to self-reports of social satisfaction and well-
being
from Survey 2 (Hypotheses 2– 4). Table 1 clarifies which
measures
were collected in each survey.
Sample
Community-dwelling adults participated in online surveys
through RAND’s American Life Panel, which constitutes a
national adult life span sample recruited through multiple
probability-based approaches such as random digit dialing and
address-based sampling (https://alpdata.rand.org/).2 Interested
in-
dividuals received equipment and Internet access, if needed.
Sub-
sets of panel members are invited to participate in regular
online
surveys for about $20 per 30 min.
Our Survey 1 sample included 496 participants who completed
the social network questions in 2011–2013, of 581 invited panel

1 Survey 1 was designed to examine the role of perceived social
network
vaccine coverage in vaccination decisions (Bruine de Bruin,
Parker, Gale-
sic, & Vardavas, 2019; Parker et al., 2013). Survey 2 was
designed to track
the effect of the financial crisis on finances and well-being
(Hurd et al.,
2015).
2 Random digit dialing and address-based sampling methods
tend to
recruit community-dwelling adults and exclude individuals in
nursing
homes, dormitories, and prisons. The longitudinal nature of the
panel does
create the opportunity for a panel member to transition from
independent
living to other housing conditions. However, RAND’s American
Life
Panel does not collect information about these housing
conditions.
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1 ROI CALCULATION AND BUSINESS CASE 1ROI CALCULATION AND BUSIN.docx

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