“Role of mobile marketing in improving customer experience for electronic gad...Pramod Patil
The purpose of this paper is to find out the role of mobile or smart phones in improving customer experience in retail shopping in India. To compete successfully in this business era, the retailer must focus on the customer’s buying experience.This paper focuses on the role of mobile or smart phones in the retail environment and how they can shape customer experiences and behaviors. Superior customer experience will result in higher customer satisfaction, more frequent shopping visits, larger wallet shares, and higher profits.
The growing use of Internet in India provides varied opportunities for online shopping from both customer and seller perspective. If Electronic marketers (E-Marketers) know the factors affecting online Indian behavior, the relationships between these factors and the type of online buyers, they can further develop their marketing strategies to convert potential buyers into active buyerswhile retainingits original customer base. This study focuses on the factors which online buyers takes into consideration while shopping online. This research will help in finding the impact of e-market on customers’ purchasing patterns and how their security and privacy concerns about online marketinginfluences their online buying behavior. The study will further encompass the various important inputs which will equip the marketers for creating online marketing more lucrative and assured by adding value to the existing services.
Capgemini has been tracking consumer shopping since 2002, gathering insights into the changing patterns of purchasing behavior from traditional high-street to multi-channel shopping.
Our most recent research - the Digital Shopper Relevancy Report 2014 - surveyed more than 18,000 digital shoppers from 18 countries.
Read the report to find out the role and use of digital channels (and devices), across the consumer purchasing journey today and in the future.
“Role of mobile marketing in improving customer experience for electronic gad...Pramod Patil
The purpose of this paper is to find out the role of mobile or smart phones in improving customer experience in retail shopping in India. To compete successfully in this business era, the retailer must focus on the customer’s buying experience.This paper focuses on the role of mobile or smart phones in the retail environment and how they can shape customer experiences and behaviors. Superior customer experience will result in higher customer satisfaction, more frequent shopping visits, larger wallet shares, and higher profits.
The growing use of Internet in India provides varied opportunities for online shopping from both customer and seller perspective. If Electronic marketers (E-Marketers) know the factors affecting online Indian behavior, the relationships between these factors and the type of online buyers, they can further develop their marketing strategies to convert potential buyers into active buyerswhile retainingits original customer base. This study focuses on the factors which online buyers takes into consideration while shopping online. This research will help in finding the impact of e-market on customers’ purchasing patterns and how their security and privacy concerns about online marketinginfluences their online buying behavior. The study will further encompass the various important inputs which will equip the marketers for creating online marketing more lucrative and assured by adding value to the existing services.
Capgemini has been tracking consumer shopping since 2002, gathering insights into the changing patterns of purchasing behavior from traditional high-street to multi-channel shopping.
Our most recent research - the Digital Shopper Relevancy Report 2014 - surveyed more than 18,000 digital shoppers from 18 countries.
Read the report to find out the role and use of digital channels (and devices), across the consumer purchasing journey today and in the future.
E - Commerce StrategiesDefinition and origin of Omni-channel Ret.docxjacksnathalie
E - Commerce Strategies
Definition and origin of Omni-channel Retailing
Omni-channel alludes to a multi-channel way to deal with transactions that aim to furnish the client with the shopping of items. It equips the customer with the ability of either purchasing items online from a cell phone or a desktop. Also, omni-channel refers to beyond ordering on the telephone. In regards to Omni-channel, customers can shop in bricks and mortar store or by phone. It is with this characteristic and capability enabled to clients in the shopping process thus eventually defines the term Omni-channel retailing.
It is a marketing strategy that began in 2003 whereby it has progressed from a new idea to in trendy vogue expression, to a fundamental part of effective promoting. Its origin was not only ventured into by one business but by rivals who competed in regards to the market price, the quality of items produced and sold, finally the rivals aimed at getting more buyers. Therefore, Omni-channel began and mainly based itself on Customer Centricity in stores (Bernstein, 2008).
Omni-channel origin was figured out by ‘Best Buy’ when they understood they couldn't beat Walmart on cost. Hence, the procedure wandered by Best Buy went for contending with Walmart to out destroy them web retailing. It is in such manner that innovation can obscure the qualification in the middle of online and physical retailing, consequently empowering the retailers and their store network accomplices reexamine their focused techniques.
Current issues in Omni-channel retailing:
As of now, most retailers and vendors are "Omni-channel" in their conduct and viewpoint. It is because they are significantly wandering into the disconnected from the net and online retails channel to do their showcasing and deals to customers. These features of omnichannel have helped the retailers and merchants in their new environment, thus can prosper through reconsidering their methodologies for conveying items and data to their customers (Bell, D., Gallia, S., Moreno, & A., 2014).
There is a rise of a non-significant market share of the physical stores, the small merchants, and retailers from the channel integration. With the ascent in the notoriety of omnichannel retailing, adding brick and mortar stores to existing systems, for example, sites or indexes expands brand incomes in a global setting. The retailers advocate an upper hand through channel combination of both logged off and web retailing. It has prompted the readiness of the clients paying for goods across many channels (Herhausen, et al., 2015). The many channels are online and offline businesses that sell variety items without any boundaries.
Developments need to address industry, and administrative based difficulties all together to encourage the globalization of business sectors. Particular changes must be consolidated in the current full grown, rising and less created markets.It 's hard to start a new business model combining online sales ...
In a new report, titled “Digital Shopper Relevancy,” Capgemini surveyed 16,000 digital shoppers across 16 developing and mature markets about their use of different channels and devices for shopping.
Informes PwC - Encuesta Total Retail GlobalPwC España
El informe "Hacia un modelo de Total Retail", elaborado por PwC, analiza las expectativas y hábitos de consumo del comprador online, a partir de 15.000 entrevistas a compradores digitales de todo el mundo, y las implicaciones para las compañías del sector de distribución y consumo en los próximos años.
Informe de PwC sobre las expectativas y hábitos de consumo del comprador onlineMaría Bretón Gallego
El informe Hacia un modelo de ‘Total Retail’, elaborado por PwC, analiza las expectativas y hábitos de consumo del comprador online, a partir de 15.000 entrevistas a compradores digitales de todo el mundo, y las implicaciones para las compañías del sector de distribución y consumo en los próximos años.
Internet y las nuevas tecnologías han multiplicado la influencia del consumidor, pero, ¿qué les están pidiendo a las marcas? Las nuevas expectativas y hábitos del consumidor digital tendrán importantes implicaciones para las compañías del sector en los próximos años
This project was ideated and executed by me and my mentor who helped in the successful completion of the summer project. This was done during my last term in BBA as a part of my curriculum.The aim was to draw a conclusion on the preference between the above mentioned mode of shopping for clothes within my district Nadia. The study was conducted with the use of a survey form which was designed by me and simple factor analysis which will definitely be useful for future business development and also the consumers.
WalmartPositioning for Parent’s ChoiceTanena Terrell.docxcelenarouzie
Walmart
Positioning for Parent’s Choice
Tanena Terrell
Positioning Presentation
MTK/421
Kelly Duman
Introduction
This is a Walmart brand that focuses on baby products
The products include diapers and other accessories
It is a product of Wyeth
Parent’s choice is a brand sold by Walmart and it basically deals with baby products. It provides a wide range of products to give parents various options to choose from
*
Target Market
With respect to demographics, the product targets consumers from all societies
Basically, they need to have a stable source of income that will enable them to buy the products
The brand targets consumers who have a stable source of income from which they can purchase the different products for their children
*
Cont’d
Geographically, the product is targeted to parents across the globe
Provided they have children, the products are meant for them
The product is universal
Parents across the world need these products for their children, therefore, Parent’s Choice does not have geographical limitations with respect to who it targets
*
Cont’d
As far as psychographic factors are concerned, the brand products are designed for all parents
They should be interested in high-quality products
The brand’s products are of exceptional quality, therefore, the targeted market should believe in high-quality products
*
Cont’d
As per behavioral segmentation the brand looks at customers who are interested in the benefits of the product
Behavioral segmentation basically looks at the behavior of the consumers
The different products offered by the brand are effective, therefore, it targets consumers that are interested in the benefits that they will get from products
*
Perceptual Map
The perceptual map lists competing products with respect to how consumers look at them. The products’ competitiveness is in the following order; from the most competitive to the least competitive: Pampers, Mee mee, Parent’s Choice, Pigeon, Sebamed, Mothercare, and Biotique
*
Cont’dWith respect to the perceptual map, Pampers is the top competitor in the list as it offers the best quality productsBiotique is the least competitive because it has the lowest quality in the list
The perceptual creates a pictorial representation of how different competing brands and products are viewed in the market
*
ConclusionThe perception of brands greatly depends on the prices that they are offered (Kerin, Roger, Hartley, Steven, & Rudelius, 2015)Most customers assume that the most expensive products are of the best qualityManufacturers need to balance quality and price to create the best perception
The price at which a product is sold determines how it is perceived in the market. Consumers tend to create a relationship between the price and quality of a product (Kerin, Roger, Hartley, Steven, & Rudelius, 2015). The create a direct relationship.
*
References
Kerin, Roger A., Hartley, Steven W., & Rudelius, W. (2015). Marketing, 12th ed. McGra.
People have changed the way they purchase things. Rather than going to the nearest store to research and make a purchase, customers now prefer to research online and then buy in-store, or vice versa. With the increasing popularity and use of mobile technology, people expect buying things from wherever they are and whenever they want to.
The global retail sector now faces unprecedented changes and upheaval, with a broad set of technologies, influenced by social and economic trends, set to determine future.
A presentation of a college project explaining the issue of local vendors during the covid . We have presented a solution in the form of an android app which will help the local vendors to stay in the market of internet beside big giants like grofers, big basket and all others with a different approach.
‘ICHAPTER TWOChapter Objectives• To define stakeholdLesleyWhitesidefv
‘I
CHAPTER TWO
Chapter Objectives
• To define stakeholders and understand
their importance
• To distinguish between primary and
secondary stakeholders
To discuss the global nature of
stakeholder relationships
To consider the impact of reputation and
crisis situations on social responsibility
performance
To examine the development of
stakeholder relationships
To explore how stakeholder relationships
are integral to social responsibility
Chapter Outline
Stakeholders Defined
Stakeholder Identification and Importance
Performance with Stakeholders
Development of Stakeholder Relationships
Implementing a Stakeholder Perspective in
Social Responsibility
Link between Stakeholder Relationships and
Social Responsibility
Opening Vignette
The Fight against Childhood Obesity
America’s children are growing, not in height or intel
lectual capacity but in weight. Advertising of fast food
and highly processed, corn syrup—laced foods is at the
heart of the controversy. While TV advertising of food
and restaurants has dropped 34 percent from 1977 to
2004, the use of the internet, promotions, school adver
tising and vending machines, and sponsored sports sta
diums is on the rise. Childhood obesity has become such
a concern that First Lady Michelle Obama has created
the movement Let’s Movel to encourage the develop
ment of a healthier generation of children. Regulators,
parents, and our society in general are concerned about
the health of our children, It is estimated that medi
cal costs associated with childhood obesity will total
$19,000 over a person’s lifetime.
Studies conducted by the Kaiser Family Foundation
have found that the average child sees around 40,000
advertisements per year on television—most of these
encourage children to consume candy, cereal, fast food,
and soft drinks. What seems to be particularly prob
lematic is the use of popular licensed children’s cartoon
characters (e.g., SpongeBob SquarePants and Scooby
Doo) to advertise these unhealthy foods. Critics believe
food manufacturers are not being socially responsible
by encouraging children to eat food that is detrimental
to their health. Companies are choosing to do some
thing about this problem.
A study over a five-year period revealed that
16 major food and beverage companies—including
PepsiCo, Coca-Cola, and Bumble Bee Foods—have
reduced calories in foods amounting to an average of
78 calories a day from the American diet. For instance,
Nestlé used new technology to reduce fat by half and
calories by one-third in their “Slow Churned” Edy’s and
Dreyer’s ice cream. What is especially important is that
these 16 companies account for about 36 percent of
calories in packaged foods.
Changes are also being made in advertising. The
Walt Disney Company mandated that the company will
no longer allow sponsorships or advertisements on its
networks for foods that do not meet certain nutritional
criteria. It also pledged to reduce the calories in foods
sold at its theme parks. Coca- ...
More Related Content
Similar to ⁎ Corresponding author.E-mail addresses [email protected] (
E - Commerce StrategiesDefinition and origin of Omni-channel Ret.docxjacksnathalie
E - Commerce Strategies
Definition and origin of Omni-channel Retailing
Omni-channel alludes to a multi-channel way to deal with transactions that aim to furnish the client with the shopping of items. It equips the customer with the ability of either purchasing items online from a cell phone or a desktop. Also, omni-channel refers to beyond ordering on the telephone. In regards to Omni-channel, customers can shop in bricks and mortar store or by phone. It is with this characteristic and capability enabled to clients in the shopping process thus eventually defines the term Omni-channel retailing.
It is a marketing strategy that began in 2003 whereby it has progressed from a new idea to in trendy vogue expression, to a fundamental part of effective promoting. Its origin was not only ventured into by one business but by rivals who competed in regards to the market price, the quality of items produced and sold, finally the rivals aimed at getting more buyers. Therefore, Omni-channel began and mainly based itself on Customer Centricity in stores (Bernstein, 2008).
Omni-channel origin was figured out by ‘Best Buy’ when they understood they couldn't beat Walmart on cost. Hence, the procedure wandered by Best Buy went for contending with Walmart to out destroy them web retailing. It is in such manner that innovation can obscure the qualification in the middle of online and physical retailing, consequently empowering the retailers and their store network accomplices reexamine their focused techniques.
Current issues in Omni-channel retailing:
As of now, most retailers and vendors are "Omni-channel" in their conduct and viewpoint. It is because they are significantly wandering into the disconnected from the net and online retails channel to do their showcasing and deals to customers. These features of omnichannel have helped the retailers and merchants in their new environment, thus can prosper through reconsidering their methodologies for conveying items and data to their customers (Bell, D., Gallia, S., Moreno, & A., 2014).
There is a rise of a non-significant market share of the physical stores, the small merchants, and retailers from the channel integration. With the ascent in the notoriety of omnichannel retailing, adding brick and mortar stores to existing systems, for example, sites or indexes expands brand incomes in a global setting. The retailers advocate an upper hand through channel combination of both logged off and web retailing. It has prompted the readiness of the clients paying for goods across many channels (Herhausen, et al., 2015). The many channels are online and offline businesses that sell variety items without any boundaries.
Developments need to address industry, and administrative based difficulties all together to encourage the globalization of business sectors. Particular changes must be consolidated in the current full grown, rising and less created markets.It 's hard to start a new business model combining online sales ...
In a new report, titled “Digital Shopper Relevancy,” Capgemini surveyed 16,000 digital shoppers across 16 developing and mature markets about their use of different channels and devices for shopping.
Informes PwC - Encuesta Total Retail GlobalPwC España
El informe "Hacia un modelo de Total Retail", elaborado por PwC, analiza las expectativas y hábitos de consumo del comprador online, a partir de 15.000 entrevistas a compradores digitales de todo el mundo, y las implicaciones para las compañías del sector de distribución y consumo en los próximos años.
Informe de PwC sobre las expectativas y hábitos de consumo del comprador onlineMaría Bretón Gallego
El informe Hacia un modelo de ‘Total Retail’, elaborado por PwC, analiza las expectativas y hábitos de consumo del comprador online, a partir de 15.000 entrevistas a compradores digitales de todo el mundo, y las implicaciones para las compañías del sector de distribución y consumo en los próximos años.
Internet y las nuevas tecnologías han multiplicado la influencia del consumidor, pero, ¿qué les están pidiendo a las marcas? Las nuevas expectativas y hábitos del consumidor digital tendrán importantes implicaciones para las compañías del sector en los próximos años
This project was ideated and executed by me and my mentor who helped in the successful completion of the summer project. This was done during my last term in BBA as a part of my curriculum.The aim was to draw a conclusion on the preference between the above mentioned mode of shopping for clothes within my district Nadia. The study was conducted with the use of a survey form which was designed by me and simple factor analysis which will definitely be useful for future business development and also the consumers.
WalmartPositioning for Parent’s ChoiceTanena Terrell.docxcelenarouzie
Walmart
Positioning for Parent’s Choice
Tanena Terrell
Positioning Presentation
MTK/421
Kelly Duman
Introduction
This is a Walmart brand that focuses on baby products
The products include diapers and other accessories
It is a product of Wyeth
Parent’s choice is a brand sold by Walmart and it basically deals with baby products. It provides a wide range of products to give parents various options to choose from
*
Target Market
With respect to demographics, the product targets consumers from all societies
Basically, they need to have a stable source of income that will enable them to buy the products
The brand targets consumers who have a stable source of income from which they can purchase the different products for their children
*
Cont’d
Geographically, the product is targeted to parents across the globe
Provided they have children, the products are meant for them
The product is universal
Parents across the world need these products for their children, therefore, Parent’s Choice does not have geographical limitations with respect to who it targets
*
Cont’d
As far as psychographic factors are concerned, the brand products are designed for all parents
They should be interested in high-quality products
The brand’s products are of exceptional quality, therefore, the targeted market should believe in high-quality products
*
Cont’d
As per behavioral segmentation the brand looks at customers who are interested in the benefits of the product
Behavioral segmentation basically looks at the behavior of the consumers
The different products offered by the brand are effective, therefore, it targets consumers that are interested in the benefits that they will get from products
*
Perceptual Map
The perceptual map lists competing products with respect to how consumers look at them. The products’ competitiveness is in the following order; from the most competitive to the least competitive: Pampers, Mee mee, Parent’s Choice, Pigeon, Sebamed, Mothercare, and Biotique
*
Cont’dWith respect to the perceptual map, Pampers is the top competitor in the list as it offers the best quality productsBiotique is the least competitive because it has the lowest quality in the list
The perceptual creates a pictorial representation of how different competing brands and products are viewed in the market
*
ConclusionThe perception of brands greatly depends on the prices that they are offered (Kerin, Roger, Hartley, Steven, & Rudelius, 2015)Most customers assume that the most expensive products are of the best qualityManufacturers need to balance quality and price to create the best perception
The price at which a product is sold determines how it is perceived in the market. Consumers tend to create a relationship between the price and quality of a product (Kerin, Roger, Hartley, Steven, & Rudelius, 2015). The create a direct relationship.
*
References
Kerin, Roger A., Hartley, Steven W., & Rudelius, W. (2015). Marketing, 12th ed. McGra.
People have changed the way they purchase things. Rather than going to the nearest store to research and make a purchase, customers now prefer to research online and then buy in-store, or vice versa. With the increasing popularity and use of mobile technology, people expect buying things from wherever they are and whenever they want to.
The global retail sector now faces unprecedented changes and upheaval, with a broad set of technologies, influenced by social and economic trends, set to determine future.
A presentation of a college project explaining the issue of local vendors during the covid . We have presented a solution in the form of an android app which will help the local vendors to stay in the market of internet beside big giants like grofers, big basket and all others with a different approach.
Similar to ⁎ Corresponding author.E-mail addresses [email protected] ( (20)
‘ICHAPTER TWOChapter Objectives• To define stakeholdLesleyWhitesidefv
‘I
CHAPTER TWO
Chapter Objectives
• To define stakeholders and understand
their importance
• To distinguish between primary and
secondary stakeholders
To discuss the global nature of
stakeholder relationships
To consider the impact of reputation and
crisis situations on social responsibility
performance
To examine the development of
stakeholder relationships
To explore how stakeholder relationships
are integral to social responsibility
Chapter Outline
Stakeholders Defined
Stakeholder Identification and Importance
Performance with Stakeholders
Development of Stakeholder Relationships
Implementing a Stakeholder Perspective in
Social Responsibility
Link between Stakeholder Relationships and
Social Responsibility
Opening Vignette
The Fight against Childhood Obesity
America’s children are growing, not in height or intel
lectual capacity but in weight. Advertising of fast food
and highly processed, corn syrup—laced foods is at the
heart of the controversy. While TV advertising of food
and restaurants has dropped 34 percent from 1977 to
2004, the use of the internet, promotions, school adver
tising and vending machines, and sponsored sports sta
diums is on the rise. Childhood obesity has become such
a concern that First Lady Michelle Obama has created
the movement Let’s Movel to encourage the develop
ment of a healthier generation of children. Regulators,
parents, and our society in general are concerned about
the health of our children, It is estimated that medi
cal costs associated with childhood obesity will total
$19,000 over a person’s lifetime.
Studies conducted by the Kaiser Family Foundation
have found that the average child sees around 40,000
advertisements per year on television—most of these
encourage children to consume candy, cereal, fast food,
and soft drinks. What seems to be particularly prob
lematic is the use of popular licensed children’s cartoon
characters (e.g., SpongeBob SquarePants and Scooby
Doo) to advertise these unhealthy foods. Critics believe
food manufacturers are not being socially responsible
by encouraging children to eat food that is detrimental
to their health. Companies are choosing to do some
thing about this problem.
A study over a five-year period revealed that
16 major food and beverage companies—including
PepsiCo, Coca-Cola, and Bumble Bee Foods—have
reduced calories in foods amounting to an average of
78 calories a day from the American diet. For instance,
Nestlé used new technology to reduce fat by half and
calories by one-third in their “Slow Churned” Edy’s and
Dreyer’s ice cream. What is especially important is that
these 16 companies account for about 36 percent of
calories in packaged foods.
Changes are also being made in advertising. The
Walt Disney Company mandated that the company will
no longer allow sponsorships or advertisements on its
networks for foods that do not meet certain nutritional
criteria. It also pledged to reduce the calories in foods
sold at its theme parks. Coca- ...
– 272 –
C H A P T E R T E N
k Introduction
k Albert Ellis’s Rational Emotive
Behavior Therapy
k Key Concepts
View of Human Nature
View of Emotional Disturbance
A-B-C Framework
k The Therapeutic Process
Therapeutic Goals
Therapist ’s Function and Role
Client ’s Experience in Therapy
Relationship Between Therapist and Client
k Application: Therapeutic
Techniques and Procedures
The Practice of Rational Emotive Behavior
Therapy
Applications of REBT to Client Populations
REBT as a Brief Therapy
Application to Group Counseling
k Aaron Beck ’s Cognitive Therapy
Introduction
Basic Principles of Cognitive Therapy
The Client–Therapist Relationship
Applications of Cognitive Therapy
k Donald Meichenbaum’s Cognitive
Behavior Modifi cation
Introduction
How Behavior Changes
Coping Skills Programs
The Constructivist Approach to Cognitive
Behavior Therapy
k Cognitive Behavior Therapy
From a Multicultural Perspective
Strengths From a Diversit y Perspective
Shortcomings From a Diversit y Perspective
k Cognitive Behavior Therapy
Applied to the Case of Stan
k Summary and Evaluation
Contributions of the Cognitive Behavioral
Approaches
Limitations and Criticisms of the Cognitive
Behavioral Approaches
k Where to Go From Here
Recommended Supplementary Readings
References and Suggested Readings
Cognitive Behavior Therapy
– 273 –
A L B E R T E L L I S
ALBERT ELLIS (1913–2007)
was born in Pittsburgh but
escaped to the wilds of New
York at the age of 4 and lived
there (except for a year in New
Jersey) for the rest of his life. He
was hospitalized nine times as
a child, mainly with nephritis,
and developed renal glycosuria
at the age of 19 and diabetes at the age of 40. By rigor-
ously taking care of his health and stubbornly refusing
to make himself miserable about it, he lived an unusually
robust and energetic life, until his death at age 93.
Realizing that he could counsel people skillfully and
that he greatly enjoyed doing so, Ellis decided to become
a psychologist. Believing psychoanalysis to be the
deepest form of psychotherapy, Ellis was analyzed and
supervised by a training analyst. He then practiced psy-
choanalytically oriented psychotherapy, but eventually
he became disillusioned with the slow progress of his cli-
ents. He observed that they improved more quickly once
they changed their ways of thinking about themselves
and their problems. Early in 1955 he developed rational
emotive behavior therapy (REBT). Ellis has rightly been
called the “grandfather of cognitive behavior therapy.”
Until his illness during the last two years of his life, he
generally worked 16 hours a day, seeing many clients for
individual therapy, making time each day for professional
writing, and giving numerous talks and workshops in
many parts of the world.
To some extent Ellis developed his approach as a
method of dealing with his own problems during his
youth. At one point in his life, for example, he had exag-
ge ...
‘Jm So when was the first time you realised you were using everydLesleyWhitesidefv
‘Jm: So when was the first time you realised you were using everyday
P: First tiem I used every day, I’d met a girl, she was ten years older than me, I was twenty, she was thirty
Jm: so that’s eight years ago was it?
P: yeah yeah, met her, what happened, she had had a previous two year heroin addiction, and up to that period I had tried it but I’d never smoked it everyday, but she had obviously, and for six weeks, after meeting her we were smoking it everyday, and I’d said to her I don’t understand how people get addicted to this stuff, people must be weak, I mean I don’t understand how they’re getting addicted to this stuff, and after six weeks, what happened is I woke up and realised I’d lost all this weight, I hadn’t been to the toilet for six weeks, and also, I really really needed to go to the toilet, and I didn’t know what the feeling of clucking was, if you see what I mean, what the sensations and that felt like, and you know I can remember that very first day vividly, /just feeling that pain and the want for heroin like, erm it’s hard to explain what it feels like, erm it’s like a rushing on your mind, you can’t stop thinking about it, I want it, I want it, I want it, so obviously we had to go and score then, but that was when I had my first real feeling of it washing over me, it was actually making me feel better than normal, before previously I was getting a good buzz off it, it was giving me a good buzz like, but fromthat point on it would wash over me where I just used to feel normal again, as in, whereas before, so then my tolerance built up, then my use went up even more, I was smoking like sixty pounds worth a day, and I was committing crimes to like supply that,’
Jm: So you said there was this one day you’d woken up with a habit, had you already realised you’d been using everyday by this point?
P: yeah, yeah,
Jm: can you remember the first time you realised you were using heroin every day?
P: yeah
Jm: can you remember where you were at this time?
P: lying in bed
Jm: and do you remember exactly what you thought when you realised this?
P: I thought I gotta go and buy heroin, I gotta go and get some heroin
Jm: you said there were other times you were using every day
P: I was using every day, and I thought it was addictive, I thought it wasn’t physically addictive, I thought must have been a mentally addictive drug, and then all of a sudden I had the physical withdrawals, I realised that I was physically addicted to it,
Jm: so you woke up and felt you needed to go and get some, did you have any other thoughts about it? Like fuck I need to sort myself out?
P: yeah, basically
Jm: and when you woke up with that runny nose, was it first of all what’s wrong with me, or was it I know exactly what I need?
P: I knew what was wrong straight away. I just knew, I dunno how, I just knew it would make me feel better, I just knew it would like, I dunno why, it just did, it’s strange
Jm: About this time did you have any conversations w ...
•2To begin with a definition Self-esteem is the dispLesleyWhitesidefv
•2
“To begin with a definition: Self-esteem is the disposition to experience oneself as
being competent to cope with the basic challenges of life and of being worthy of
happiness.” (“What Self-Esteem Is and Is Not” by Dr. Nathaniel Branden, 1997,
article adapted from The Art of Living Consciously, Simon & Schuster, 1997).
•3
“Self-esteem is an experience. It is a particular way of experiencing the self. It is a
good deal more than a mere feeling — this must be stressed. It involves emotional,
evaluative, and cognitive components. It also entails certain action dispositions: to
move toward life rather than away from it; to move toward consciousness rather
than away from it; to treat facts with respect rather than denial; to operate self-
responsibly rather than the opposite.” (“What Self-Esteem Is and Is Not” by Dr.
Nathaniel Branden, 1997, article adapted from The Art of Living Consciously,
Simon & Schuster, 1997).
•4
“Self-esteem is an experience. It is a particular way of experiencing the self. It is a
good deal more than a mere feeling — this must be stressed. It involves emotional,
evaluative, and cognitive components. It also entails certain action dispositions: to
move toward life rather than away from it; to move toward consciousness rather
than away from it; to treat facts with respect rather than denial; to operate self-
responsibly rather than the opposite.” (“What Self-Esteem Is and Is Not” by Dr.
Nathaniel Branden, 1997, article adapted from The Art of Living Consciously,
Simon & Schuster, 1997).
•5
“Self-esteem is an experience. It is a particular way of experiencing the self. It is a
good deal more than a mere feeling — this must be stressed. It involves emotional,
evaluative, and cognitive components. It also entails certain action dispositions: to
move toward life rather than away from it; to move toward consciousness rather
than away from it; to treat facts with respect rather than denial; to operate self-
responsibly rather than the opposite.” (“What Self-Esteem Is and Is Not” by Dr.
Nathaniel Branden, 1997, article adapted from The Art of Living Consciously,
Simon & Schuster, 1997).
•6
“Self-esteem is an experience. It is a particular way of experiencing the self. It is a
good deal more than a mere feeling — this must be stressed. It involves emotional,
evaluative, and cognitive components. It also entails certain action dispositions: to
move toward life rather than away from it; to move toward consciousness rather
than away from it; to treat facts with respect rather than denial; to operate self-
responsibly rather than the opposite.” (“What Self-Esteem Is and Is Not” by Dr.
Nathaniel Branden, 1997, article adapted from The Art of Living Consciously,
Simon & Schuster, 1997).
“One does not need to be a trained psychologist to know that some people with low
self-esteem strive to compensate for their deficit by boasting, arrogance, and
conceited behavior.” (“What Self-Esteem ...
•2Notes for the professorMuch of the content on theseLesleyWhitesidefv
•2
Notes for the professor:
Much of the content on these slides are based on Robbins & Judge (2012)
(“Essentials of Organizational Behavior” textbook, edition 11, chapter 2: attitudes
and job satisfaction)
•3
Attitudes are evaluative statements and these statements can be favorable or
unfavorable. Individuals’ attitudes at work such as their satisfaction with their jobs
or their commitment to the organization are important because factors like job
satisfaction and organizational commitment can relate to one’s performance at
work.
According to the single component definition, attitudes constitute of only “affect”
or, in other words, of feelings we have about objects, people, or events. This single
component view simplifies things for us as it only refers to “affect” or feelings. We
tend to have complex views about the world but at the same time we want to predict
behavior. We can predict behavior by looking at one’s attitudes through identifying
one’s affect about objects, people, or events.
According to the tri-component view, which represents a more complicated view of
attitudes, attitudes consist of affect, behavior, and cognition. These are the ABC’s of
attitudes. According to this view or definition, affect includes how you feel,
behavior includes how you behave (how you behave is considered as part of your
attitude), and cognition includes your thoughts, your rationalizations. According to
the tri-component view of attitudes, one’s attitudes include one’s affect, behaviors,
and cognitions about objects, people, or events. For example, you may hate your job
(negative affect), but you may show up at work (behavior) not to get fired. You
might also have these cognitions that say “I should be happy to get this job…”. As you see in
this example, the components (affect, cognition, and behavior) may not be consistent.
An example where the components (affect, cognition, and behavior) are consistent is the
following: “I like my job (affect), I show up at work (behavior), and work is good for me
because it keeps my mind sharp and allows me to learn new skills, travel, make friends, be a
part of a social community, pay for my bills, pay for the things I want to do in my life, and
keeps me active and in the work force. Also, I should be very happy and grateful to have this
job because so many of my friends have been looking for a great job for a long time now.” In
another example, you may like smoking (affect), you may smoke a pack a day (behavior), and
you may have a cognition that says “smoking is good for me because I don’t get overweight”
or “it increases brain activity” (cognition). In both of these examples, the components (affect,
cognition, behavior) are consistent and, therefore, individuals do not experience dissonance.
However, to the extent that these components are not consistent, individuals experience
dissonance, in others words, an aversive mental state (which will be discussed in later s ...
· You must respond to at least two of your peers by extending, refLesleyWhitesidefv
· You must respond to at least two of your peers by extending, refuting/correcting, or adding additional nuance to their posts and supporting your opinion with a reference. Response posts must be at least 150 words. Your response (reply) posts are worth 2 points (1 point per response). Your post will include a salutation, response (150 words), and a reference.
· Quotes “…” cannot be used at a higher learning level for your assignments, so sentences need to be paraphrased and referenced.
· Acceptable references include scholarly journal articles or primary legal sources (statutes, court opinions), journal articles, and books published in the last five years—no websites or videos to be referenced without prior approval.
Discussion and responses must be posted in APA format for Canvas to receive full grades. Automatic deduction of 10% if not completed
Culturally Competent
Vixony Vixamar
St. Thomas University
Prof. Kathleen Price
NUR 417
October 28, 2021
Culturally Competent
The COVID-19 has affected over 45 million in the United States and has led to over seven hundred and forty thousand deaths across the United States. The pandemic has increasingly affected all individuals and has led to various economic as well as social changes. However, there have been some health disparities identified with people of color being among the most affected individuals (Reyes, 2020). Nurses are at the frontline of providing health care services to individuals that have been infected by the virus. Therefore, as a nurse, I have come across various COVID-19 cases where the patient needed to be observed or there was a need to manage the condition.
One case was that of a middle-aged pregnant woman that had contracted the virus. The symptoms started as headaches and feeling tired. She stated that she initially assumed these symptoms as normal pregnancy symptoms as she had earlier on in the week engaged in some intensive exercises as she went shopping with some family members. However, one evening she had some challenges breathing and her family members rushed her to the hospital. She had to be put on oxygen as she needed support breathing. She was given a PCR test that turned out to be negative. However, the fact that she needed to be on oxygen necessitated another test which also read negative. At this point, it was crucial that a chest scan be done to help with the diagnosis. Upon the scan, the physician diagnosed the patient with COVID-19. Her condition quickly deteriorated and she had to be put in intensive care. It was especially challenging caring for her given that she was seven months pregnant at the time. At one point, the family had contemplated terminating the pregnancy to increase her chances of surviving given that fetal movements had subsided for a while. However, after a few weeks in the intensive care unit, she made a full recovery and was able to deliver her baby full-term. She remained on oxygen and under observation until ...
· You have choices. You should answer three of the four available LesleyWhitesidefv
· You have choices. You should answer three of the four available short answer questions and one of the two essay questions. Please label each response (e.g., Short Answer 3) to indicate what question you are responding to. Please also sort your short answer responses in numerical order (so 1,2,4 if those are the three questions you answer – even if you prepared them in 4,1,2 order).
PART ONE: Answer three of the following four short answer questions. Be sure to label your answers with the question number and arrange them in question order number. A target range for responses to these questions is approximately 250 words.
Short Answer 1
History depends on the choice to narrate certain facts and omit others. All histories are incomplete, which makes the act of writing history both powerful and creative. Why does the distinction between “what happened” and “what is said to have happened” matter?
Short Answer 2
What is the “Great Man Myth” and how does that lens shape what histories get told? What histories get omitted when we focus on the Great Man Myth? Incorporate examples from at least one media technology to help support your answer.
Short Answer 3
In “The Case of the Telegraph,” James Carey argued, “The simplest and most important point about the telegraph is that it marked the decisive separation of ‘transportation’ and ‘communication.’” Describe two ideologies that were ushered in by the telegraph and how they changed society. Your answer should consider both the dominant history and also an alternative or counter history for each development.
Short Answer 4
While mainstream history celebrates photography as the first visual medium for objectivity and evidence, counter histories claim that it actually muddied the distinction between objective and subjective knowledge. Explain how photography blurred the distinction between objectivity and subjectivity and how that transmitted and influenced cultural and social ideologies. Provide specific examples to support your argument.
PART TWO: Answer one of the following two essay questions. Be sure to label your answers with the question number and arrange them in question order number.
Your answers should engage these questions at the conceptual level and use specific examples from the media histories we have covered this semester to support your arguments. A target range for this essay response is probably in the 1,200-2,000 word range.
Essay 1
In the first part of the Media Histories course, we have repeatedly turned to Benedict Anderson’s argument about imagined communities:
I propose the following definition of the nation: it is an imagined political community – and imagined as both inherently limited and sovereign.
It is imagined because the members of even the smallest nation will never know most of their fellow-members, meet them, or even hear of them, yet in the minds of each lives the image of their communication…
Communities are to be distinguished not by their ...
· You may choose one or more chapters from E.G. Whites, The MinistLesleyWhitesidefv
· You may choose one or more chapters from E.G. Whites, The Ministry of Healing. You will then write a reflection paper regarding your thoughts, meaningful ideas, feelings, and/or reactions, and the application of these to nursing practice or your own spiritual growth and self-care.
· Readings from E.G. White; The Ministry of Healing
· Chapter 19 In Contact with Nature
· Chapter 29 The Builders of the Home
· Chapter 31 The Mother
· Chapter 34 True Education, a Missionary Training
Grading Criteria
Points Possible
Points Earned/Comments
1. Paper is typed in at least 3 pages, double spaced, and turned in on time via D2L, with title page in APA format
10 Points
2. Introductory paragraph is attention-getting
10 Points
3. Spelling, grammar, mechanics, and usage are correct throughout the paper
10 Points
4. Thoughts are expressed in a coherent and logical manner.
20 Points
5. Viewpoints and interpretations are insightful, demonstrating an in-depth reflection.
20 Points
6. Concluding paragraph sums up information, reiterates ideas and opinions, and leaves the reader with a call to action or something meaningful to remember
10 Points
7. Pertinent reference sources are skillfully woven throughout paper without overuse of quotations but, rather, attempt to paraphrase
10 Points
8. References are properly cited in APA format with no plagiarism.
5 Points
9. At least 3 references are cited, including a reference from current class assigned chapter readings in White, and two journal articles of your own choice (one may be the Bible).
5 Points
Total
100 Possible Points
Actual Points =
References: White, E. G. (2011). The Ministry of healing. Guildford, UK: White Crow Books.
APA format reference that you may use for free:
https://owl.english.purdue.edu/owl/resource/560/01/
Technology in Education - Research Article
Educational data mining using cluster
analysis and decision tree technique:
A case study
Snježana Križanić
1
Abstract
Data mining refers to the application of data analysis techniques with the aim of extracting hidden knowledge from data by
performing the tasks of pattern recognition and predictive modeling. This article describes the application of data mining
techniques on educational data of a higher education institution in Croatia. Data used for the analysis are event logs
downloaded from an e-learning environment of a real e-course. Data mining techniques applied for the research are
cluster analysis and decision tree. The cluster analysis was performed by organizing collections of patterns into groups
based on student behavior similarity in using course materials. Decision tree was the method of interest for generating a
representation of decision-making that allowed defining classes of objects for the purpose of deeper analysis about how
students learned.
Keywords
Educational data mining, cluster analysis, decision trees, case study, log file
Date received: 30 September 2019; accepted: 18 ...
· · Prepare a 2-page interprofessional staff update on HIPAA andLesleyWhitesidefv
·
· Prepare a 2-page interprofessional staff update on HIPAA and appropriate social media use in health care.
Introduction
As you begin to consider the assessment, it would be an excellent choice to complete the Breach of Protected Health Information (PHI) activity. The will support your success with the assessment by creating the opportunity for you to test your knowledge of potential privacy, security, and confidentiality violations of protected health information. The activity is not graded and counts towards course engagement.
Health professionals today are increasingly accountable for the use of protected health information (PHI). Various government and regulatory agencies promote and support privacy and security through a variety of activities. Examples include:
· Meaningful use of electronic health records (EHR).
· Provision of EHR incentive programs through Medicare and Medicaid.
· Enforcement of the Health Insurance Portability and Accountability Act (HIPAA) rules.
· Release of educational resources and tools to help providers and hospitals address privacy, security, and confidentiality risks in their practices.
Technological advances, such as the use of social media platforms and applications for patient progress tracking and communication, have provided more access to health information and improved communication between care providers and patients.
At the same time, advances such as these have resulted in more risk for protecting PHI. Nurses typically receive annual training on protecting patient information in their everyday practice. This training usually emphasizes privacy, security, and confidentiality best practices such as:
· Keeping passwords secure.
· Logging out of public computers.
· Sharing patient information only with those directly providing care or who have been granted permission to receive this information.
Today, one of the major risks associated with privacy and confidentiality of patient identity and data relates to social media. Many nurses and other health care providers place themselves at risk when they use social media or other electronic communication systems inappropriately. For example, a Texas nurse was recently terminated for posting patient vaccination information on Facebook. In another case, a New York nurse was terminated for posting an insensitive emergency department photo on her Instagram account.
Health care providers today must develop their skills in mitigating risks to their patients and themselves related to patient information. At the same time, they need to be able distinguish between effective and ineffective uses of social media in health care.
This assessment will require you to develop a staff update for the interprofessional team to encourage team members to protect the privacy, confidentiality, and security of patient information.
Preparation
To successfully prepare to complete this assessment, complete the following:
· Review the infographics on protecting PHI provided in the res ...
· · Introduction· What is hyperpituitarism and hypopituitariLesleyWhitesidefv
·
· Introduction
· What is hyperpituitarism and hypopituitarism?
· Signs and symptoms
· Include all necessary physiology and/or pathophysiology in your explanation.
· How do you treat the disorder?
· Which population is at risk of developing this disorder and why
· Use appropriate master’s level terminology.
· Reference a minimum of three sources; you may cite your etext as a source. Use APA format to style your visual aids and cite your sources.
explain the processes or concepts in your using references to support your explanations.
...
· · Write a 3 page paper in which you analyze why regulatory ageLesleyWhitesidefv
·
· Write a 3 page paper in which you analyze why regulatory agencies began monitoring quality in health care, explain how regulatory agencies have impacted quality of care, and provide an evaluation of quality.
Introduction
Early attempts at quality efforts were limited to the resources, knowledge, and environment in which health care services and treatment were rendered. As medical education and research advanced so did the knowledge of and focus on quality improvement efforts. Basic functions including handwashing and sterile environments were two of the many simple advancements resulting in dramatic improvements in outcomes and overall quality.
Regulatory agencies have directly impacted health care organizations' focus on, and attention to, quality improvement. Founded in 1951, The Joint Commission offers accreditation to various health care organizations who demonstrate compliance with established regulatory standards. Combined with various government agencies, initiatives have been implemented that require health care organizations to report on quality measures, thereby making their quality performance transparent throughout the industry.
As a leader in the health care industry, understanding historical perspectives of quality, regulatory oversight, and medical malpractice will allow you to effectively lead your organization to meet or exceed its strategic goals related to improved outcomes, increased reimbursements, and reduced cost.
Demonstration of Proficiency
By successfully completing this assessment, you will demonstrate your proficiency in the course competencies through the following assessment scoring guide criteria:
· Competency 2: Explain the development of health regulation and the evolution of medical malpractice.
1. Explain the evolution of medical malpractice.
1. Analyze the development of health regulation and regulatory agencies.
1. Analyze how regulatory agencies have impacted the quality of care.
1. Evaluate ways in which quality has improved or not improved since the 1800s.
. Competency 4: Communicate in a manner that is scholarly, professional, and respectful of the diversity, dignity, and integrity of others.
2. Produce writing that conveys understanding of the topic, its context, and its relevance.
2. Use academic writing conventions such as APA formatting and citation style, or others as required.
2. Produce writing that includes minimal grammar, usage, and mechanical errors, including spelling.
Instructions
For this assessment, you will write a 3 page paper in which you:
. Explain the evolution of medical malpractice.
. Analyze why regulatory agencies began monitoring quality in health care.
. Explain how organizations like the Agency for Healthcare Research and Quality (AHRQ), the Joint Commission, and other regulatory agencies have impacted quality of care.
. Explain what is meant by "deemed status."
. Describe how current attempts at quality compare to efforts on quality in the 1800s.
. Evaluate ways in whic ...
· Write a response as directed to each of the three case studies aLesleyWhitesidefv
· Write a response as directed to each of the three case studies and save the document.
1- Analyze the ethical implications of a community health initiative to decrease the rate of teenage pregnancy by means of health education in the public schools. This community takes pride in its schools and is comprised of multiple ethnic, immigrant, religious and social groups. Use the following ethical principles in your analysis: autonomy, beneficence, nonmaleficence and justice.
Egalitarian
• The view that everyone is entitled to equal rights and equal treatment. Ideally, each person has an equal share of the goods of society, and it is the role of government to ensure that this happens. The government has the authority to redistribute wealth if necessary to ensure equal treatment. Thus egalitarians support welfare rights—that is, the right to receive certain social goods necessary to satisfy basic needs. These include adequate food, housing, education, and police and fire protection. Both practical and theoretical weaknesses are inherent in egalitarianism.
Libertarian
• The libertarian view of justice advocates for social and economic liberty. While egalitarianism lacks incentives for individuals, libertarianism emphasizes the contribution and merit of individuals (Beauchamp & Childress, 2013).
• Limited role of government
Liberal democratic
Attempts to develop a theory that values both liberty and equality
• Based on Rawl’s Theory of Justice and the “veil of ignorance.” Behind this veil, people (or their representatives) are unaware of social position, race, culture, doctrine, sex, endowments, or any other distinguishing circumstances (Rawls, 2001). This is known as the original position and is an exercise to address the inequalities and bargaining advantages that result from birth, natural endowments, and historical circumstances. Without these inequalities, all people are free and equal and can work together as citizens to decide what is fair and therefore just. Once impartiality is guaranteed, Rawls suggests all rational people will choose a system of justice containing the following two principles:
• Each person has the same claim to a fully adequate scheme of equal basic liberties, and this scheme is compatible with the same scheme of liberties for all.
• Social and economic inequalities are to satisfy two conditions: first, they are to be attached to offices and positions open all under conditions of fair equality of opportunity; and second, they are to be to the greatest benefit to the least advantaged members of society (the difference principle).
Box 7.2
Ethical Principles
Respect for autonomy: Based on human dignity and respect for individuals, autonomy requires that individuals be permitted to choose those actions and goals that fulfill their life plans unless those choices result in harm to another.
Nonmaleficence: Nonmaleficence requires that we do no harm. It is impossible to avoid harm entirely, but t ...
· Write a brief (one paragraph) summary for each reading.· · RLesleyWhitesidefv
· Write a brief (one paragraph) summary for each reading.
·
· Respond to any one of the following reflective prompts and respond.
· McLaughlin et al. (2013) discuss ways in which to summatively assess student learning using performance-based assessment tasks. When students are tasked with designing and building simple machines, what is actually being assessed during these tasks? As you consider using performance-based assessment tasks in your future instruction, what are some advantages compared to traditional assessments (e.g., paper and pencil tests)? What are some disadvantages of using performance-based assessments? Describe how you might use a summative performance-based assessment in Field Assignment 2, being specific about what you are assessing (e.g., science topic, science skill).
· Castaneda and Bautista (2011) address growing concerns of assessment surrounding ELLs, focusing on the need to evaluate students based on their level of language proficiency. This is rooted in the need to differentiate not only our instruction, but our assessments. In order to do this, the authors propose four strategies. Consider your future teaching and describe how you plan to address each of these four strategies to assess your ELL students based on their level of language proficiency. To contextualize your response, focus on your upcoming Field Assignment 2 - describe your assessment plan for ELLs for that particular lesson.
3 PARAGRAPHS TOTAL
1 page
A fourth-grade
lesson on simple
machines integrates
performance
assessment tasks.
More and more science teachers are integrating perfor-mance assessment tasks into their lessons. These tasks are a means of assessing conceptual understanding while
providing students with various opportunities to demonstrate
learning outcomes. Performance assessment tasks typically
engage students in authentic, real-world, hands-on learning
situations and impose high cognitive demands resulting in
meaningful learning (Darling-Hammond 2004). Information
gleaned from performance assessments not only support sci-
ence teachers’ understandings of the strengths and weaknesses
of the students but also guide their instruction in ways that will
develop the knowledge and mental skills required to construct
appropriate mental models for authentic performance situa-
tions. Performance assessment tasks comprise a performance
that may be observed and/or a tangible product that may be
examined (Bass, Contant, and Carin 2009). Examples include
oral presentations, debates, exhibits, written products, con-
struction of models, and solutions to problems. In creating ef-
fective performance tasks, science teachers should consider the
following factors: the focus of the task, the context of the task,
directions provided for the students and the rubric used for as-
sessment. The focus of the assessment task should be closely
aligned with the learning objectives and the context should
provide a background and a que ...
· Write a 2-page single spaced (12 font Times New Roman) book repoLesleyWhitesidefv
· Write a 2-page single spaced (12 font Times New Roman) book report on the key highlights. Mentioned five major topics that you liked and how you plan to use them to develop yourself and your career.
BOOK SUMMARY: (key highlights)
Techniques in Handling People :
-Don’t criticize, condemn or complain.
-Give honest and sincere appreciation.
-Arouse in the other person an eager want.
Six ways to Make People Like You :
-Become genuinely interested in other people.
-Smile.
-Remember that a person’s name is to that person the sweetest and most important sound in any language.
-Be a good listener. Encourage others to talk about themselves.
-Talk in terms of the other person’s interests.
-Make the other person feel important – and do it sincerely.
Win People to Your Way of Thinking:
-The only way to get the best of an argument is to avoid it.
-Show respect for the other person’s opinions. Never say, “You’re wrong.”
-If you are wrong, admit it quickly and emphatically.
-Begin in a friendly way.
-Get the other person saying “yes, yes” immediately.
-Let the other person do a great deal of the talking.
-Let the other person feel that the idea is his or hers.
-Try honestly to see things from the other person’s point of view.
-Be sympathetic with the other person’s ideas and desires.
-Appeal to the nobler motives.
-Dramatize your ideas.
-Throw down a challenge.
Be a Leader: How to Change People Without Giving Offense or Arousing Resentment:
-Begin with praise and honest appreciation.
-Call attention to people’s mistakes indirectly.
-Talk about your own mistakes before criticizing the other person.
-Ask questions instead of giving direct orders.
-Let the other person save face.
-Praise the slightest improvement and praise every improvement. Be “hearty in your approbation and lavish in your praise.”
-Give the other person a fine reputation to live up to.
-Use encouragement. Make the fault seem easy to correct.
-Make the other person happy about doing the thing you suggest.
Criticism
“Criticism is futile because it puts a person on the defensive and usually makes him strive to justify himself. Criticism is dangerous, because it wounds a person’s precious pride, hurts his sense of importance, and arouses resentment. …. Any fool can criticize, condemn and complain—and most fools do. But it takes character and self-control to be understanding and forgiving.”
People are Emotional
“When dealing with people, let us remember we are not dealing with creatures of logic. We are dealing with creatures of emotion, creatures bristling with prejudices and motivated by pride and vanity.”
The Key to Influencing Others
“The only way on earth to influence other people is to talk about what they want and show them how to get it.”
The Secret of Success
“If there is any one secret of success, it lies in the ability to get the other person’s point of view and see things from that person’s angle as well as from your own.”
FMM 325
Milestone Three
Megan Georg ...
· Weight 11 of course gradeInstructionsData Instrument and DLesleyWhitesidefv
· Weight: 11% of course grade
Instructions
Data Instrument and Data Collection Tool
For this assignment, you will complete another portion of the research paper, which will be included in your final paper in Unit VII. In part one of this assignment, you will describe your data instrument. In part two, you will provide the data collection tool that will be used in your research study (remember this is a hypothetical research study that you will not conduct).
For part one, Data Instrument, provide the following:
· What type of research will be conducted (qualitative, quantitative)?
· Is this a questionnaire with open-ended or close-ended questions or an interview?
· Will there be a questionnaire, face-to-face interviews, or the use of the telephone or mail?
· Will there be an interview (one-on-one or group)?
· Who is the study population?
For part two, Data Collection Tool, provide the following:
· Give a short introduction on your research; provide the purpose of your study and why you chose to conduct it.
· Explain how long participation will take.
· Explain how you will avoid sampling bias.
· Provide a minimum of ten (10) questions for your questionnaire.
Submit a two to three-page paper (page count does not include title and references pages). Please adhere to APA Style when creating citations and references for this assignment. APA formatting, however, is not necessary.
Resources
10/5/2021 Assignment Print View
https://ezto.mheducation.com/hm.tpx?todo=c15SinglePrintView&singleQuestionNo=2.&postSubmissionView=13252714224874008,13252714225034381&wid=13252717358425567&role=student&pid=34975829_51290… 1/4
Problem-Solving Application Case—
Incentives Gone Wrong, then Wrong
Again, and Wrong Again
The Wells Fargo scandal demonstrates how a company’s choice and implementation of performance management incentives can have
disastrous side effects. This activity is important because it illustrates why managers must never implement an incentive scheme without
considering as much as possible any and all effects that it may have on employees’ behavior.
The goal of this activity is for you to understand the link between the details of Wells Fargo’s incentive scheme and the employee behaviors that
resulted from it.
Read about how performance incentives led to scandal at Wells Fargo. Then, using the three-step problem-solving approach, answer the
questions that follow.
Money is an important tool for both attracting and motivating talent. If you owned a company or were its CEO, you would likely agree and
choose performance management practices to deliver such outcomes. It also is possible you’d use incentives to help align your employees’
interests, behaviors, and performance with those of the company. After all, countless companies have used incentives very successfully, but not
all. The incentives used by Wells Fargo had disastrous consequences for employees, customers, and the company itself.
The Scenario and Behaviors
A client enters a ...
· Week 3 Crime Analysis BurglaryRobbery· ReadCozens, P. M.LesleyWhitesidefv
· Week 3: Crime Analysis: Burglary/Robbery
· Read:
Cozens, P. M., Saville, G., & Hillier, D. (2005). Crime prevention through environmental design (CPTED): A review and modern bibliography. Property Management, 23(5), 328-356. Retrieved from https://search-proquest-com.ezproxy1.apus.edu/docview/213402232?accountid=8289
Famega, C. N., Frank, J., & Mazerolle, L. (2005). Managing police patrol time: The role of supervisor directives. Justice Quarterly : JQ, 22(4), 540-559. Retrieved from https://search-proquest-com.ezproxy1.apus.edu/docview/228177475?accountid=8289
Zhang, C., Gholami, S., Kar, D., Sinha, A., Jain, M., Goyal, R., & Tambe, M. (2016). Keeping pace with criminals: An extended study of designing patrol allocation against adaptive opportunistic criminals. Games, 7(3), 15. doi:http://dx.doi.org.ezproxy1.apus.edu/10.3390/g7030015
Lesson Introduction
After reading this week’s materials, you will be able to define the role of police patrol and its importance as applied to law enforcement intelligence.
Lesson Objectives
● Outline and discuss early police and patrol procedures
● Evaluate modern patrol allocations
Course Objectives that apply to this lesson:
CO: (3) Demonstrate an understanding of the history of police patrol procedures from the days of early policing to modern day policing allocations.
Patrol
There are many ways to determine the best way to allocate patrol resources in a community. Some of them are covered in our studies but that is not the whole story. Keep in mind that it is more likely to be a combination of models as well as a sensitivity to specific to regional and demographic considerations.
It is important to take many variables into consideration when determining how best to utilize patrols. At the same time, we must remember to expect the unexpected and be as prepared as possible to respond. No two situations, weeks, months, or years will ever be exactly the same. This is part of what makes a career in criminal justice such a challenge and also so rewarding.
In the early 1900’s and before the work of August Vollmer, there was not much information concerning police allocation. Vollmer created a list of police functions such as crime prevention, criminal investigation, traffic control, and patrol. In the early deployment allocation models, the police were distributed based on calls for service and officer workloads. Although what appeared to be effective at the time, more research began to see potential issues with this model such as police saturation may cause a higher number of arrests. Other departments in this time frame distributed patrol units evenly without taking into account other factors such as crimes, population, distance, or number of personnel.
Preventative Patrol
As police operations moved forward, other methods of deployment emerged. In the 1960’s, law enforcement professional started to shift focus on preventative patrol methods. As discussed in previous lessons, t ...
· What does the Goodale and Humphrey (1998) article mean by the fLesleyWhitesidefv
· What does the Goodale and Humphrey (1998) article mean by “the field’s preoccupation with vision as sight?"
· How did Goodale and Humphrey’s view of the ventral and dorsal visual stream differ from the earlier theory of Ungerleider and Mishkin (1982)?
· Discuss the evidence presented by Goodale and Humphrey to support their view. How has learning about the brain’s two separate visual systems changed the way you think about your own visual experience?
· Finally, Goodale and Humphrey (1998) refer to the two visual systems as having evolved. Compare and contrast the evolutionary approach to function of the brain with the Tripartite Man’s approach.
The objects of action and perception
Melvyn A. Goodale*, G. Keith Humphrey
Department of Psychology, University of Western Ontario, London, ON N6A 5C2, Canada
Abstract
Two major functions of the visual system are discussed and contrasted. One function of
vision is the creation of an internal model or percept of the external world. Most research in
object perception has concentrated on this aspect of vision. Vision also guides the control of
object-directed action. In the latter case, vision directs our actions with respect to the world by
transforming visual inputs into appropriate motor outputs. We argue that separate, but inter-
active, visual systems have evolved for the perception of objects on the one hand and the
control of actions directed at those objects on the other. This ‘duplex’ approach to high-level
vision suggests that Marrian or ‘reconstructive’ approaches and Gibsonian or ‘purposive-
animate-behaviorist’ approaches need not be seen as mutually exclusive, but rather as com-
plementary in their emphases on different aspects of visual function. 1998 Elsevier Science
B.V. All rights reserved
Keywords:Vision; Action; Perception
1. Introduction
It is a common assertion that the fundamental task of vision is to construct a
representation of the three-dimensional layout of the world and the objects and
events within it. But such an assertion begs at least two fundamental and interrelated
questions. First, what is vision? Second, what is the nature of the representation that
vision delivers? These questions, which are central to the entire research enterprise
in understanding human vision, form the framework for the present paper. In
attempting to answer these questions, we will contrast what we believe are two
major functions of the visual system. One function of vision is the creation of an
internal model or percept of the external world – a model that can be used in the
0010-0277/98/$19.00 1998 Elsevier Science B.V. All rights reserved
PII S 0 0 1 0 - 0 2 7 7 ( 9 8 ) 0 0 0 1 7 - 1
C O G N I T I O N
Cognition 67 (1998) 181–207
* Corresponding author. Tel.: +1 519 6612070; fax: +1 519 6613961; e-mail: [email protected]
recognition of objects and understanding their interrelations. Most research in object
vision has concentrated on this function (witness the current vol ...
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3. dramatically over the last few years, and now tops the agenda of
all major grocery retailers (Warschun 2012). “[Grocery]
retailers
are increasingly finding they must innovate in ways that make it
easier and more convenient for their customers to get what they
need without missing a beat," according to Nielsen's Continuous
Innovation report, which found that “convenience itself may be
the most creative and energetic example of retail innovation”
(Nielsen 2014). Of these convenience-oriented retail
innovations,
the shift towards multichannel offline-online retailing is one of
the most important and successful practices. Several of the large
grocery retail chains (such as Walmart, Tesco and Ahold) now
(‘brick and click’ grocery retailers). By increasing their service
levels, multichannel retailers aim to retain existing customers
and gain new customers in the increasingly competitive retail
environment (Chintagunta, Chu, and Cebollada 2012; Kabadayi,
Eyuboglu, and Thomas 2007; Neslin and Shankar 2009; Zhang
et al. 2010).
Customers clearly appreciate and take advantage of this
extended service. The large majority of online grocery shoppers
are multichannel shoppers who visit both the online and offline
channel, thereby combining convenience advantages of online
shopping with self-service advantages of offline stores (Alba
et al. 1997; Chu, Chintagunta, and Cebollada 2008; Chu et al.
2010; Konuş, Verhoef, and Neslin 2008; Venkatesan, Kumar,
and Ravishanker 2007). Although multichannel shoppers visit
both channels, their purchase behavior tends to differ across the
online and offline channel, both in the tendency to buy certain
categories and in the sensitivity to marketing mix instruments.
For instance, a product's online intangibility can result in
low(er)
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Marketing 31 (2015) 63–78
online purchase shares, especially for sensory categories that
consumers prefer to physically examine before purchasing them
(Degeratu, Rangaswamy, and Jianan 2000). Bulky and heavy
categories, in contrast, tend to be top-selling categories in
online
stores because of the high online shopping convenience benefits
(Chintagunta, Chu, and Cebollada 2012). Prior research has also
shown that households tend to be more brand loyal and size
loyal, but less price sensitive in the online channel than in the
offline channel (Chu et al. 2010). Because channel differences
in
assortment and price can vary across categories, this may also
influence consumers' allocation patterns over the online and
offline channel. As a result, the multichannel shopping context
clearly adds to the complexity of retailers' management
decisions, and multichannel grocery retailers need more insight
into how shoppers allocate their purchases across their online
and
offline stores (cf. Dholakia et al. 2010; McPartlin and Dugal
2012; Shankar and Yadav 2010).
The purpose of this study is to improve the understanding of
multichannel shopping behavior and to provide a better insight
into the underlying mechanisms and factors that determine how
5. multichannel shoppers allocate their category purchases across
the online and offline channel. Building on the multiple store
and online shopping literature, we analyze the impact on
purchase allocation patterns at the category level, and take
‘traditional’ marketing mix based factors as well as ‘intrinsic’
category characteristics into account. Given that online grocery
shopping is still in the ‘innovation stage’ (small, but rapidly
increasing number of consumers who start buying groceries
online), our model explicitly accounts for dynamic adjustments
of allocation patterns as consumers gain more experience with
buying groceries online. We also account for the possibility that
managers adjust category assortment and pricing decisions to
anticipated channel differences in buying behavior, and correct
for potential endogeneity biases in marketing mix effects.
Our research provides important contributions to the marketi ng
and retailing literature. First, we extend insights from the
multiple
store shopping literature by examining category allocation
decisions in a substantially different multichannel retail
context,
with fundamental differences in the factors driving purchase
allocation decisions. Second, we add to the multichannel
literature
by providing a comprehensive analysis of the factors that can
cause differences in online purchase tendency across grocery
categories. As indicated in previous (offline) purchase behavior
studies (Hoyer and MacInnis 2010), grocery shopping differs
substantially from other purchase contexts. As the same
products
are purchased repeatedly, purchase involvement tends to be low,
and consumers are not prepared to spend much time and effort
to
search for the ‘best’ product. Findings of previous multichannel
studies – which mainly focused on durable goods – are therefore
not directly transferrable to, and provide little insight into, what
6. drives purchase allocation decisions in a multichannel grocery
shopping context. The limited number of studies on
multichannel
purchases of groceries focused on specific issues such as
channel
differences in sensitivity to specific marketing mix instruments
(e.g., price sensitivity: Chu, Chintagunta, and Cebollada 2008;
Chu et al. 2010), the degree of brand exploration across both
channels (Chu et al. 2010; Pozzi 2012) or the impact of
transaction
costs on channel choice (Chintagunta, Chu, and Cebollada
2012).
While useful to develop expectations on the impact of specific
factors, they do not provide insights into the overall purchase
patterns of multichannel shoppers. Third, we refine and extend
previous research on online buying experience effects (Ansari,
Mela, and Neslin 2008; Frambach, Roest, and Krishnan 2007;
Kim, Ferrin, and Raghav Rao 2008) by examining experience
effects on category level purchase decisions and by taking
different possible effects of experience into account.
From a managerial point of view, our results help multichannel
retailers to improve the mix of customer services and enhance
their overall value proposition for multichannel shoppers
(Zhang
et al. 2010). Our results can guide online category management
and promotional decisions of multichannel retailers to stimulate
online purchases. Striving for larger online shopping baskets
can
be beneficial and generate additional revenue that may cover the
high fixed costs that online retailers face (e.g., storing and
delivery
costs). Next, by obtaining a better insight into the effects of
experience on different types of factors that influence
consumers'
category purchase allocation decisions, multichannel retailers
7. can
better assess the importance of stimulating trial and repeat
purchases (to generate positive experience effects) vs. taking
corrective actions (e.g., adjust channel differences in assortment
and/or price).
Conceptual Framework
In this section, we provide a conceptual framework on how
multichannel shoppers allocate category purchases across the
online and offline channel operated by a single retailer. We take
the overall allocation of grocery purchases across channels
(channel choice and visit frequency) as given and examine
whether and how category-specific allocation factors lead to
deviations from the overall allocation scheme (i.e., result in
disproportionately low or high channel shares in category
purchases). Building on the multiple store and multichannel
shopping literature, we explain category allocation decisions as
the outcome of a shopping utility maximization process that
accounts for (i) acquisition utility, i.e., the benefits that
consumers
receive (e.g., product quality and promotions) and the costs they
need to give up (e.g., price) when acquiring the product, and
(ii) transaction utility, i.e., the benefits consumers receive
(e.g., time-saving home delivery systems) and the cost they
need
to bear (e.g., perceived risk of online ordering) when
transferring
the products from the store to home (Baltas, Argouslidis, and
Skarmeas 2010; Chintagunta, Chu, and Cebollada 2012; Gupta
and Kim 2010; Vroegrijk, Gijsbrechts, and Campo 2013).
Below,
we identify the major acquisition and transaction utility related
factors and discuss how they are expected to influence category
allocation patterns over the online and offline channel. Next, we
discuss how online buying experience in the category plays a
8. moderating role (see also Fig. 1).
Acquisition Utility: The Impact of Marketing Mix Instruments
Studies on multiple store shopping behavior in an offline
context have demonstrated that marketing mix based differences
Fig. 1. Conceptual framework & expected effects.
65K. Campo, E. Breugelmans / Journal of Interactive Marketing
31 (2015) 63–78
in acquisition utility – such as assortment and price differences
–
are important drivers of category allocation decisions across
stores (Gijsbrechts, Campo, and Nisol 2008; Vroegrijk,
Gijsbrechts, and Campo 2013). As explained in more detail
below, even though online and offline stores that belong to the
same chain have a similar price/quality positioning, marketing
mix instruments can still differ across channels for several
reasons (Neslin et al. 2006; Wolk and Ebling 2010). In the
following, we discuss the impact of channel differences in
assortment, price and promotion intensity (Fox and Hoch 2005)
and examine the differential effect of in-store incentives aimed
at stimulating unplanned purchases on allocation decisions
(Breugelmans and Campo 2011).
Assortment Differences
Online and offline assortments can differ in size for several
reasons. On the one hand, online stores provide the opportunity
to
carry a larger assortment as a result of the online store's
limitless
shelves. On the other hand, cost and demand constraints, and
9. the
need to respect very short delivery times, can be reasons to
restrict
online assortments for some categories (such as groceries). The
literature on assortment effects suggests that larger assortments
tend to be preferred over smaller ones because they offer more
choice flexibility and enhance feelings of autonomy (Oppewal
and Koelemeijer 2005; Sloot, Fok, and Verhoef 2006)1. We
expect that channel differences in assortment size can influence
channel allocation decisions, such that consumers are more
1 While larger assortments may also come at the cost of more
difficult
evaluation processes because of information overload, choice
conflict or regret
(Dhar 1997; Huffman and Kahn 1998), the general expectation
appears to be
that the advantages of larger assortments tend to cancel out
potential
disadvantages (cf. negative effects of assortment reductions on
category sales;
Borle et al. 2005; Sloot, Fok, and Verhoef 2006).
inclined to buy the category in the channel that offers the
largest
assortment.
Price Differences
Multichannel retailers can charge different prices in their
online and offline channel in view of cost and demand
considerations (Neslin and Shankar 2009; Wolk and Ebling
2010). For one, the online channel may entail higher operational
costs, including additional ICT, picking, handling and delivery
costs. At the same time, the online channel may experience cost
savings as the result of lower store layout, display and shelf
replenishment costs, and because price adjustments can literally
be executed by pressing a button. In addition, several studies
10. provided evidence of channel differences in price sensitivity
(Chu, Chintagunta, and Cebollada 2008; Wolk and Ebling
2010).
Multichannel grocery retailers can incorporate these cost and
price sensitivity differences in product prices to safeguard
profit
margins (compensate for higher online operational costs) or to
stimulate online purchases (let consumers benefit from lower
online operational costs or use different price levels to exploit
price sensitivity differences). Similar to assortment differences,
we assume that multichannel shoppers will incorporate price
differences in their category allocation decisions, and allocate a
lower share of category purchases to the channel where the
category is least attractive in price (cf. multiple store shopping
literature; Gijsbrechts, Campo, and Nisol 2008; Vroegrijk,
Gijsbrechts, and Campo 2013).
Promotion Differences
The intensity of promotional actions can differ between the
online and offline channel of the same retailer to account
for differences in price/promotion sensitivity across channels
(Wolk and Ebling 2010) or for more pragmatic reasons such as
Image of Fig. 1
66 K. Campo, E. Breugelmans / Journal of Interactive
Marketing 31 (2015) 63–78
different account managers being in charge of the promotion
planning in each channel (Avery et al. 2012). Consumers can
react by temporarily adjusting their allocation patterns to take
advantage of more attractive promotional actions in one of both
channels.
In-store Stimuli
In-store stimuli may trigger a forgotten need or new idea.
11. Compared to the offline channel, online shoppers tend to be
less sensitive to these in-store stimuli for several reasons: they
can more easily control their shopping route and immediately
navigate to the needed category by clicking the category's
page; they do not have to wait at fresh meat/fish counters or at
the cash register (locations that are often used to store impulse
products) and the more ‘functional’ online shopping
environment
can evoke a more goal-oriented shopping attitude making
consumers more reluctant to deviate from their purchase plans
and give in to impulse purchases (Babin and Darden 1995). We
therefore expect that the online store will obtain a lower share
of
purchases for impulse categories that consumers do not usually
plan in advance to buy and for which they tend to be very
sensitive towards in-store stimuli.
Transaction Utility: The Impact of Perceived Purchase Risk
and Shopping Convenience
Multichannel studies have indicated that channel differences
in transaction costs can depend on the categories that need to be
purchased and are mainly based on two components: (i)
perceived
purchase risk and (ii) shopping convenience (Chintagunta, Chu,
and Cebollada 2012; Gupta and Kim 2010). Online purchases
can
be associated with a higher perceived purchase risk as a result
of the products' intangibility, i.e., the lack of sensory decision
cues (Degeratu, Rangaswamy, and Jianan 2000; Laroche et al.
2005). On the other hand, online shopping provides convenience
advantages through the possibility of having products picked up
by online grocery staff and having them delivered at home (Chu
et al. 2010; Gupta and Kim 2010).
Perceived Purchase Risk
The lack of sensory information in the online store can
12. constitute an important disadvantage for sensory categories –
such as fresh meat, vegetables and fruit – that tend to be
evaluated
prior to purchase based on sensory information cues (Degeratu,
Rangaswamy, and Jianan 2000; Hoch 2002; Laroche et al. 2005;
Peck and Childers 2003). Not being able to see or touch
products
can complicate the evaluation process and lead to greater
uncertainty and a higher perceived risk of online purchases
(Laroche et al. 2005; Pauwels et al. 2011; Weathers, Sharma,
and
Wood 2007). This may increase the transaction costs of buying
sensory products in the online store (Gupta and Kim 2010) and
result in relatively lower online purchase shares of sensory
categories compared to other categories (Chintagunta, Chu, and
Cebollada 2012).
Shopping Convenience
The shopping convenience advantage of online stores may
especially benefit bulky and heavy categories since online
shopping eliminates the burden of physically handling these
products, e.g., putting them into the basket and carrying them
home. The resulting increase in transaction utility can lead to
disproportionately higher online category purchase shares of
bulky and heavy categories (Chintagunta, Chu, and Cebollada
2012).
Moderating Impact of Online Buying Experience
Because online shopping for groceries is lagging behind
compared to other categories (McPartlin and Dugal 2012),
many consumers are still relatively new to and unfamiliar with
the online grocery store environment and shopping process.
Consequently, they may adjust their purchase behavior as they
gain more experience with buying groceries online. For this
13. reason, and given that the online purchase tendency can differ
across grocery categories, we include category-specific online
buying experience as a moderator of category allocation
decisions. Based on the previous discussion and consumer
behavior literature, we postulate that experience can work in
different ways: (i) reduce the uncertainty and perceived risk of
online purchases (Frambach, Roest, and Krishnan 2007;
Iyengar,
Ansari, and Gupta 2007; Kim, Ferrin, and Rao 2008), (ii) help
to gain additional factual and choice-related knowledge (Alba
and Hutchinson 1987; Iyengar, Ansari, and Gupta 2007) and
(iii) involve a learning process in which consumers adjust their
evaluation and decision processes to the new store environment
(Degeratu, Rangaswamy, and Jianan 2000; Hamilton and
Thompson 2007; Hoch 2002). Experience can thus attenuate as
well as reinforce category differences in online purchase share,
or
it may not affect the allocation pattern at all when no risk is
involved or no learning process is needed.
We expect that experience has a mitigating effect on the
reluctance to buy sensory categories online. First, conditional
upon a positive and satisfying outcome, experience can enhance
confidence in the online purchase outcome and increase trust in
the retailer's selection and delivery process (cf. Kim, Ferrin,
and
Raghav Rao 2008; Urban, Amyx, and Lorenzon 2009). Second,
experience helps with ‘learning’ to infer missing information
from other – verbal and visual – cues that can be easily
accessed
in the online store and that are diagnostic of the product's
quality
(e.g., quality labels, product characteristics that act as a quality
cue such as brand names and expiration dates) (Degeratu,
Rangaswamy, and Jianan 2000; Laroche et al. 2005; Peck and
Childers 2003).
14. On the other hand, we expect that consumers may not be
able to accurately assess assortment size and price differences
between the online and offline channel from the start. For low
involvement, multi-category purchases such as groceries,
consumers may not be able or motivated to go through a
complete evaluation of the entire assortment, and hence, may
not be fully aware of actual assortment or price differences.
After some online purchases in the category, they may
gradually become aware that some items are missing or only
67K. Campo, E. Breugelmans / Journal of Interactive Marketing
31 (2015) 63–78
available in the online assortment, or that some items are higher
or lower priced online (Alba and Hutchinson 1987; Hoyer and
MacInnis 2010). As a result, consumers may adjust their
channel preferences and purchase allocation pattern, and these
experience-based corrections in assortment and price percep-
tions may thus reinforce initial assortment and price effects.
Finally, we expect that sales promotions, in-store stimuli
and the convenience of buying bulky/heavy categories are
easy to evaluate without much online shopping experience.
Hence, there is no incentive to learn and adjust the shopping
process, and the reaction to these factors is expected to be
immediate and independent of a consumer's online shopping
experience.
Model
To examine multichannel category allocation decisions, we
focus on the online channel's share in category spending (SCS),
taking overall spending at the chain as given. Using a relative
instead of absolute measure of online category expenditures has
15. the advantage of removing the effect of customer and category
differences in total spending. In line with multiple store
shopping
literature (Gijsbrechts, Campo, and Nisol 2008; Vroegrijk,
Gijsbrechts, and Campo 2013), we concentrate on allocation
patterns over a longer period of time (i.e., bi-weekly periods, t),
rather than category purchase decisions on a visit-by-visit basis.
In addition, because consumers only have to decide how to
allocate their purchases within this two-week period when they
plan to buy the category and when they visit both channels, we
focus on observations with (i) a category need (i.e., an online
and/
or offline purchase in the category) and (ii) an online and
offline
store visit (i.e., a multichannel shopping period where
consumers
are in the opportunity to buy the product online and/or offline
and allocation is not pre-defined to 0% or 100%). This allows
us to eliminate both the effect of a consumer's general online
buying tendency (decision to visit the online store) and the
effect of category purchase decisions on observed category
allocations.
The online channel's share in spending for category c in
period t for household i (SCSit
c ) is defined and estimated over
all categories simultaneously (pooled estimation)2:
SCScit ¼
eU
c
it
1 þ eUcit : ð1Þ
16. By using a logistic model in Eq. (1), we ensure that the values
of the outcome variable are restricted within the zero–one
range.
To linearize the model, we use the method of log-centering
(Cooper and Nakanishi 1996; Lesaffre, Rizopulos, and Tsonaka
2007), that has been applied in many other studies (see
2 To simplify the discussion, we use an overall index t and c for
time periods
and categories respectively. As we only include multichannel
purchase
occasions (periods where household i visited both channels),
and categories
for which the household made a purchase within this period, the
time index is
actually household-specific while the category index is
household- plus time-
specific.
e.g., Cleeren, van Heerde, and Dekimpe 2013; Leenheer et al.
2007):
ln
SCScit
1−SCScit
� �
¼ Vcit þ μcit: ð2Þ
To avoid that the dependent variable in Eq. (2) is equal to the
log of zero (SCSit
c equal to zero) or an undefined value (division
by zero, SCSit
c equal to one), we add a small amount to the
17. numerator and denominator of Eq. (2) (cf. Bass et al. 2009;
Cleeren, van Heerde, and Dekimpe 2013), such that:
ln
SCScit þ 0:001
1−SCScit þ 0:001
� �
¼ Vcit þ μcit: ð2′Þ
We use consumer, marketing mix and experience as
explanatory variables:
Vcit þ μcit ¼ γ0i þ γ1 � STSit þ γ2 � Expcit þ γ3 � Usageci
� �
þ δ1 � Assc þ δ2 � Pricec þ δ3 � Promoc þ δ4 � ISSc½ �
þ δ5 � Sensc þ δ6 � Bulky Heavyc½ � þ μcit:
ð3Þ
The first square brackets in Eq. (3) capture consumer
characteristics that account for individual differences in the
tendency to allocate purchases in category c to the online
channel,
including a consumer-, category- and time-specific online
buying
experience variable (Expit
c), and a usage variable capturing the
consumer's overall experience with the category (Usagei
c). In
addition, we include the online store's share in total spending in
period t for consumer i (STSit), defined as the overall
percentage
18. of online purchases in total grocery expenditures of consumer i
at
the chain in period t. Including this variable allows capturing
category-specific deviations from the overall online/offline
allocation pattern that result from channel differences in
acquisition and transaction utility. The second square brackets
include variables that may entail channel differences in
acquisition
utility, i.e., category-specific channel differences in assortment
size (Assc), price (Pricec), promotion (Promot
c), and in-store
stimuli (ISSc). The third square brackets capture the effect of
transaction cost related characteristics, including whether the
category is a sensory (Sensc), or bulky/heavy (Bulky_Heavyc)
category. We describe the operationalization of these variables
in
the Data section. μit
c is a normally-distributed error term.
To incorporate the effect of category-specific online buying
experience, we use a model with varying coefficients (Foekens,
Leeflang, and Wittink 1999; Kopalle, Mela, and Marsh 1999).
The parameters of the category-specific variables are a function
of experience, allowing the effect to increase or decrease with
higher levels of online buying experience in the category:
δq ¼ δq0 þ δq1 � Expcit; q ¼ 1–6ð Þ: ð4Þ
Next, because channel differences in assortment and price
variables can be inspired by management expectations on
multichannel purchase behavior, we control for potential
19. 68 K. Campo, E. Breugelmans / Journal of Interactive
Marketing 31 (2015) 63–78
endogeneity of these variables using a control function ap-
proach (Luan and Sudhir 2010; Petrin and Train 2010)3. Web
appendix A provides more detailed information. Our final model
includes the residuals of the control function models of
assortment
(Res_Assc) and price (Res_Pricec) as additional variables:
Vcit ¼ γ0i þ γ1 � STSit þ γ2 � Expcit þ γ3 � Usageci
� �
þ ½δ1 � Assc þ δ2 � Pricec þ δ3 � Promoc þ δ4 � ISSc�
þ δ5 � Sensc þ δ6 � Bulky Heavyc½ �
þ ½θ1 � Res Assc þ θ2 � Res Pricec�:
ð3′Þ
Finally, to capture unobserved heterogeneity, we use (i) latent-
class estimation, allowing the parameters of explanatory
variables
to vary across latent segments (Andrews, Ainslie, and Currim
2002; Kamakura and Russell 1989), and (ii) a random
coefficient
approach by introducing a standard normally distributed latent
factor (Fi), allowing intercepts to vary across households
(Vermunt and Magidson 2013). We formulate the household-
specific intercept in Eq. (3′) as:
γ0i ¼ γ01 þ γ02 � Fi: ð5Þ
We use Latent GOLD® software to compute the latent factor
and estimate the coefficient γ02 (while fixing the value of the
standard deviation of the latent factor to 1; see Vermunt and
Magidson 2013, p 100–101). Latent GOLD® uses a factor-
analytic parameterization of the random-intercept model. The
parameter γ02 can be interpreted as the standard deviation of
20. the
random intercept. The significance of the parameter gives an
indication of the importance of household differences in the
share
they allocate to the online store. A non-significant parameter,
corresponding to a zero standard deviation of the intercept,
points
to homogeneous online purchase tendencies.
The log-likelihood function defined by Eq. (3) and Eqs. (2′),
(3′), (4), and (5) is given by:
LL ¼
X
i
ln
X
s
Pi sð Þ∏t∏c f ln
SCScit þ 0:001
1−SCScit þ 0:001
� �����Vcit;s
� �
;
ð6Þ
where Vit,s
c is the segment-specific version of Eq. (3′) that allows
21. for differences between segments in their sensitivity to factors
that affect channel allocation decisions, f is the joint density
3 We expect that the endogeneity problem is especially
important for the
assortment and price variables because these are typically long-
term strategic
decisions where the offline channel's price and assortment are
taken into
account. Promotions, on the other hand, are expected not to
have an
endogeneity problem because they are short-term decisions
made independently
from the decisions in the other channel. Estimation of a control
function model
for promotion intensity indeed provided extremely low
explanatory value, and
robustness checks confirmed that no improvements in fit or
substantive results
can be gained when controlling for endogeneity in the
promotion variable.
function of the normal distribution and Pi(s) is the (a priori )
probability that household i belongs to segment s, which is
defined as:
Pi sð Þ ¼
eφsXR
r¼1e
φr
; ð7Þ
where φs reflects the size (importance) of segment s and R is
the
total number of segments. Eq. (7) indicates that segments are
defined over a household's complete purchase history, i.e., over
all time periods t and categories c.
22. Data
Our data come from a major European grocery chain which
has a prominent presence throughout the country and is one of
the leading offline and online grocery retailers. As we focus on
online and offline stores of a single retail chain, online and
offline assortments mainly differ in size and not in composition
(the online assortment is a subset of the offline assortment), and
category prices are directly comparable (price differences are
not linked to quality differences). When an online order gets
placed, professional shoppers (pickers) fill the order from an
independent warehouse; the retailer then delivers the order to
the place and at the time specified by the consumer. The online
store operates independently and is given full control over
merchandising decisions. As a consequence and notwithstanding
the similarities in chain policy, there are differences between
the
online and offline channel in assortment size, product prices
and
promotional actions.
We used loyalty card information to link online and offline
purchase data over a one-year period (2006). To get stable
model estimations and a representative sample of multichannel
shoppers, we focus on households that made (i) at least two
online and two offline store visits during the estimation period
(thereby excluding one-off online trial purchases), and (ii) at
least two purchases in the category (irrespective of the channel,
to include heavy as well as light buyers of the category). In the
model estimations, we made a further selection and only focus
on bi-weekly periods (of retained households) with a visit to
both channels and a category purchase in at least one of the
channels. During these periods, the household needs the
category, but allocation is not predetermined as would be the
case in online-only (100% online) or offline-only (0% online)
23. periods. Table 1 gives an overview of the 25 frequently-
purchased
categories that were used, and indicates per category the
number
of households and observations retained.
As Table 1 indicates, most categories that we examined are
purchased during multichannel shopping occasions on a regular
basis: on average 32% of all transactions are multichannel
transactions (min. 24% for vegetables and max. 40% for water).
Online-only shopping occasions occur least often (on average
12%; min. 1% for fresh fish and max. 20% for water), while
offline-only shopping occasions are most common (on average
57%; min. 40% for water and max. 70% fresh fish). In general,
consumers are more likely to visit (and purchase categories in)
the offline channel than the online channel: the average number
Table 1
Descriptives across the 25 categories.
Category # of HH retained that # of bi-weekly periods with
category purchase
at (% of total transactions with category purchase)
Purchase frequency
(average # of bi-weeks/
year with cat. purch.)
Online category share of spending
Purchase cat. ≥2 times
and have ≥1 multichannel
transaction
27. 3
1
(2
0
1
5
)
6
3
–
7
8
Table 2
Variable notation & description.
Notation Name Description Formula
SCSit
c Share in category spending of
consumer i for category c in period t
Online spending in category c by customer i in period t
(Spendingit
online,c) divided by overall spending (online and
offline: Spendingit
online,c + Spendingit
offline,c) in category c for
consumer i in period t. (online and offline prices are measured
in constant prices; period t are bi-weekly periods where the
consumer visited the online and offline store and made a
28. purchase in the category in the online and/or offline store).
SCScit ¼
Spendingonline;cit
Spendingonline;cit þ Spending
offline;c
itð Þ
STSit Share in total spending of consumer i
in period t
Online spending across all categories by customer i in period t
(Spendingit
online) divided by the overall grocery spending (online and
offline: Spendingit
online + Spendingit
offline) for consumer i in period t.
STSit ¼ Spending
online
it
Spendingonlineit þ Spending
offline
itð Þ
Assc Assortment difference for category
c
Assortment difference ratio (number of SKUs in category c in
the online store divided by the number of SKUs in category c in
the offline store).
29. Assc ¼ Assonline;c
Assoffline;c
Pricec Price difference for category c The unit price difference
(difference between online and offline
average unit prices computed over a common set of category
products, i.e., the set of products that are available in both
channels).
Pricec = Priceonline,c − Priceoffline,c
Promot
c Online share in promotion intensity
for category c in period t
‘Share-of-voice’ based variable, measured as the share in
overall category promotions of the online store (number of
SKUs on promotion in category c in the online store in period t,
divided by the number of SKUs on promotion in category c i n
the online and offline store combined in period t; equal to 0 in
case there were no promotions in the category).
Promoct ¼
NrPromoonline; ct
NrPromoonline; ct þ NrPromooffline; ct
ISSc In-store stimuli dummy variable
for category c
Indicator variable equal to 1 if sensitivity towards in-store
stimuli is high for category c, 0 elsewhere.
Sensc Sensory dummy variable for
category c
30. Indicator variable equal to 1 if category c is a sensory category,
0 elsewhere.
Bulky_Heavyc Bulky/heavy dummy variable for
category c
Indicator variable equal to 1 if category c is a bulky or heavy
item category, 0 elsewhere.
Expit
c Online buying experience of
consumer i for category c in period t
Weighted sum of previous online purchases in category c for
consumer i in period t (bi,t − 1
c ), with weights equal to λ
(between 0 and 1) and based on all the previous periods (s = 1,
…,
t − 1) to capture fading effects, and Expi1
c as starting value based
on an initialization period of 26 bi-weeks (we used λ = .7 and
checked the results' sensitivity via robustness checks).
Expcit ¼ λ � Expci;t−1 þ λ � bci;t−1 ¼
∑s¼t−1s¼1 λ
s � bci;t−s þ λt−1 � Expci;1
Usagei
c Online usage level of consumer i
for category c
Indicator variable of whether consumer i is a heavy user of
category c based on the estimation period.
31. 4 We have detailed offline assortment and price information for
one time
period only and therefore had to use time-independent price and
assortment
variables. However, for the retailer under consideration, regular
price and
assortment within a category hardly changed during our
observation period. In
addition, we only have category-level data and are constrained
in making
marketing mix variables individual-specific (e.g., by using
SKU-weights).
5 We explicitly checked whether price differences between the
online and
offline channel were related to the online assortment reduction
strategy (e.g.,
only the more expensive items in the online assortment) and
found that this was
not the case since the online assortment of all categories covers
a range of items
with different price levels.
70 K. Campo, E. Breugelmans / Journal of Interactive
Marketing 31 (2015) 63–78
of bi-weeks per year with a purchase in the category equals 4.66
for the online channel and 9.69 for the offline channel. The
online category share of spending equals 33% (min. 5% for
fresh fish and max. 56% for water) across all bi-weekly periods
with a category purchase and increases to 51% (min. 8% for
fresh fish and max. 84% for water) for the multichannel periods
only.
Table 2 describes the details of the variable operationalization.
The share in category spending is operationalized as the ratio of
32. online purchases in category c by consumer i in period t,
divided
by the consumer's overall category purchases during that period
in the online and offline channel combined. As we focus on
multichannel shopping occasions, consumers may distribute
purchases over both channels (share of online category spending
between zero and one), but they can also decide to all ocate the
purchases to one of both channels (share of online category
spending equal to zero or one).
Marketing mix information was obtained via the retailer. As
a measure of channel differences in assortment size, we used
the ratio of the assortment size (number of SKUs) of category c
in the online store divided by the assortment size (number
of SKUs) of category c in the offline store4. This ratio is
comparable across categories, and is smaller (larger) than one
when the online assortment is smaller (larger) than the offline
assortment. To capture the category price variable, we compute
the difference in average category prices between online and
offline stores (average price for the set of category products
that
is available in both channels)5. To capture promotion effects,
we use the share in overall category promotions of the online
store, defined as the number of SKUs on promotion in category
c at time t in the online store, divided by the number of SKUs
71K. Campo, E. Breugelmans / Journal of Interactive Marketing
31 (2015) 63–78
on promotion in category c at time t in the online and offline
store combined. This eliminates the effect of differences in
assortment size and makes the variable comparable across
product
categories. The in-store stimuli variable is operationalized as a
dummy variable that is equal to one when purchases of category
33. c
are often unplanned and strongly influenced by in-store stimuli.
This classification was checked by survey data, where a
representative convenience sample of respondents assessed on a
7-point Likert scale the extent to which a category is bought
spontaneously when seeing it in the store (t = −7.41, p b .01).
The categories that were classified as ‘high in-store sensitive’
match those where the majority of the respondents indicated
they
often buy these categories without having planned the purchase.
Sensory and bulky/heavy characteristics are captured by dummy
variables equal to one when the category is classified as sensory
or bulky/heavy. Like for the in-store stimuli variable, we
checked
the sensory classification with survey data, where a
representative
convenience sample of respondents was asked to rate each
category on the importance of physical inspection of sensory
attributes prior to purchase (t = −15.684, p b .001). Bulky/heavy
categories are categories for which more than 75% of online
shoppers in our dataset buy package sizes that exceed a certain
weight (e.g., multi-packs) or that are considered as bulky
according to management.
To capture online buying experience, we use the weighted
sum of previous online purchases in the category (cf. Foekens,
Leeflang, and Wittink 1999), and use an initialization period of
26 bi-weeks to compute the starting value6. The experience
variable increases with the number of previous purchases
(frequency effect), but each previous purchase receives a weight
that becomes smaller when the purchase occurred longer ago
(recency effect) (see Table 2). The resulting experience measure
is
larger when the customer has purchased the category more often
and more recently in the online store, and varies substantially
across households and over time (range = [0, 2.33], mean = .46,
34. standard deviation = .58). Finally, category-specific usage is
operationalized as the average spending of consumer i in
category
c divided by the global average for category c, to make the
variable comparable across categories.
Table 3 classifies the categories according to marketing mix
differences and sensory, heavy/bulky and impulse
characteristics.
The classification clearly shows that there is sufficient variation
across the different characteristics. On average, online assort-
ments tend to be smaller while online prices tend to be higher.
Several other online grocery chains follow a similar strategy
(Cheng 2010). The degree of assortment reduction and the size
of
the online price premium, however, substantially differ across
categories.
Empirical Results
Estimation results of the control function models can be found
in Web Appendix A. We estimated the endogeneity-corrected
6 We have one year of data (2006) on online and offline
category purchases
that allows us to derive multichannel occasions. But, we have
one additional
year (2005) of online data that allows us to initialize the
experience variable.
version of the SCS model with a varying number of latent
classes.
Although additional segments provide a further improvement in
goodness-of-fit, there is a clear elbow (Fig. 2) in the graph of
the
Bayesian Information Criteria (BIC) statistic at four segments
with additional segments providing only a minor improvement
in
fit. The BIC statistic also indicates that the correction for
35. endogeneity improves the results (BIC of four-segment model
without vs. with endogeneity correction: 253,836 vs. 253,828).
Overall the model explains the differences in allocation pattern
across categories and consumers very well (pseudo R2 = .48).
To
investigate to what extent product category characteristics,
experience effects and household characteristics contribute to
the model's explanatory power, we examined the variance
decomposition. Results of partial model estimations indicate
that
each of these explanatory variables significantly improves
goodness-of-fit, both based on Radj
2 and likelihood ratio statistics.
The increase in Radj
2 (LR statistic) for instance, amounts to .18
(LR = 10,574; p b .005) for product characteristics (compared to
an intercepts-only model), to .04 (LR = 2,888, p b .005) for
experience (compared to a model with intercepts and product
characteristics) and to .08 (LR = 5,594, p b .005) for household
characteristics other than experience (compared to a model with
intercepts, product characteristics and experience effects). We
also conducted several robustness checks to verify the validity
of
our model and the consistency of our findings. They are
summarized in Web Appendix B. Table 4, Panel A reports the
estimation results for the homogeneous model as well as for the
four-segment model. As we will focus on the results of the
four-segment model, we first describe the differences across
segments, and next provide a general discussion of the main and
interaction (experience) effects.
Overall, in terms of segment differences, we find that
segment 1 customers (29% of all customers) are most sensitive
to purchase allocation factors (assortment, promotion, in-store
36. stimuli, sensory and bulky/heavy), and make the strongest
(effect-
reducing) adjustments when they gain more online buying
experience. Segment 2 customers (22%) are sensitive to price
differences, in-store stimuli, sensory and bulky/heavy allocation
factors, but are less sensitive to experience effects than segment
1,
which can be explained by the low overall increase in online
buying experience (see below). Segments 3 and 4 (14% and 35%
of the customers respectively) are both much less sensitive to
the
examined allocation factors than customers of the other
segments
(significant effects are limited to in-store stimuli and bulky/
heavy), but differ between each other in online buying
experience
reactions. While higher levels of experience have almost no
effect
on segment 3 consumers, segment 4 customers adjust their
reaction to channel price differences, in-store stimuli, sensory
and
bulky/heavy categories in a positive way.
We thus observe differences between consumer segments in
online buying experience effects: (i) attenuating effects that
reduce category differences in purchase allocation (segments 1
and 4), (ii) reinforcing effects that increase category differences
in purchase allocations (segment 2), and (iii) no or limited
adjustment effects (segment 3). Table 4, Panel B provides an
overview of segment characteristics that can explain these
differences in reactions. Segments 1 and 4 both allocate a large
Table 3
Classification of 25 categories.
37. Category Assortment reduction (low/high) a Price difference
(low/high) b Impulse (yes/no) Sensory (yes/no) Bulky/heavy
(yes/no)
Fresh meat High High No Yes No
Charcuterie High High No Yes No
Fresh fish High High No Yes No
Fruit Low Low No Yes No
Vegetables High Low No Yes No
Bakery pastry High Low Yes Yes No
Fat Low Low No No No
Cheese High High No Yes No
Milk Low Low No No No
Yoghurt High Low No No No
Canned fruit & vegetables High High No No No
Condiments & sauces Low High No No No
Breakfast cereals Low High No No No
Biscuits High High Yes No No
Pastes & rice High High No No No
Chocolate Low High Yes No No
Hot beverages Low High No No No
Water Low Low No No Yes
Juice Low Low No No No
Soft drinks Low Low No No Yes
Pet food Low High No No No
General body care High High No No No
Washing products Low Low No No No
Toilet paper High Low No No Yes
Cleaning products Low High No No No
a The low and high assortment reduction cover the range of
.461–.614 and .060–.459, respectively.
b The low and high price difference cover the range of .000–
.289 and .320–2.000, respectively.
38. 72 K. Campo, E. Breugelmans / Journal of Interactive
Marketing 31 (2015) 63–78
share of purchases to the online channel, and their level of
online
buying experience increases substantially over the estimation
period. In addition, segment 4 already had a relatively high
level
of experience at the start, which can explain the smaller number
of significant main effects (the experience-reducing effects have
to some extent already taken place). We label segment 1 as ‘new
online grocery fans’ and segment 4 as ‘experienced online
grocery fans’. Compared to segments 1 and 4, segments 2 and 3
both allocate a low(er) share to the online channel in general,
which may explain the absence of experience-reducing effects.
In
contrast to segment 3, segment 2 customers' online experience
level remains low, which may additionally signal a low interest
in
the online channel and thus could explain experience-
reinforcing
Fig. 2. Model goodness-of-fit.
effects. We label segment 2 as ‘online grocery skeptics’ and
segment 3 as ‘occasional online grocery shoppers’.
In terms of model estimation results, we find that the latent
factor coefficient is significant for all segments, indicating that
there is still some ‘unobserved’ (unexplained) variation across
households in the overall tendency to spend a larger SCS online.
However, comparison of the magnitude of this coefficient
(which
captures the standard deviation of the intercept over
households;
see Model section) with that of the segment-specific intercept
(i.e., the constant which captures the average effect) indicates
that
the model explains a large part of the (observed) household
39. variation in online buying tendency. We further obtain
significant
and expected positive effects for the control variables, share in
total spending (STSit) and experience (Expit
c), across all four
segments. The category usage level (Usaget
c), on the other hand,
is negative and significant for two out of four segments. A
possible explanation for this negative effect could be that heavy
users, who buy the category more frequently, buy a lower share
online because they have more opportunities to buy the category
in the offline store.
In terms of the impact of acquisition utility factors, we find
that assortment differences have a weakly significant and
positive
main effect in one segment (segment 1, δ10,s1 = 6.710, p b .10),
and a significant and positive experience interaction effect for
two other segments (segment 2: δ11,s2 = 5.439, p b .10;
segment
3: δ11,s3 = 1.729, p b .01). These results indicate that the
online
channel captures a larger share of category purchases in
categories where the online assortment is more similar in size to
the offline assortment for 3 out of the 4 segments (65% of the
consumers), but for some customers (segments 2 and 3, 36%)
Image of Fig. 2
Table 4
Model estimation results.
Variables Homog. model Four-segment model
41. −.519 ⁎ ⁎ .470 ⁎ ⁎
Bulky/heavy (δ60) 2.867 ⁎ ⁎ ⁎ 2.118 ⁎ ⁎ ⁎ 5.212 ⁎ ⁎ ⁎ 4.156
⁎ ⁎ ⁎ .681 ⁎ ⁎
Bulky/heavy ⁎ experience (δ61) −.855 ⁎ ⁎ ⁎ −.848 ⁎ ⁎ ⁎
−9.724 ⁎ ⁎ ⁎ −.762 ⁎ ⁎ ⁎ .552 ⁎ ⁎ ⁎
Residual assortment (θ1) 2.023 −.195 4.682 7.085 ⁎ −.078
Residual price (θ2) −.326 ⁎ ⁎ −.194 1.569 ⁎ ⁎ ⁎ −.763 ⁎ ⁎
−1.316 ⁎ ⁎ ⁎
Segment membership (φs) 29% 22% 14% 35%
BIC 256,333.8 253,828.3
Panel B: Segment characteristics
Variables Four-segment model
Seg. 1 Seg. 2 Seg. 3 Seg. 4
Average online buying exp first 4 bi-weeks .339 .128 .394 .451
Average online buying exp last 6 bi-weeks .490 .191 .668 .837
Change in average online buying exp .151 .063 .274 .386
Total online spending amount (€) 932.69 401.47 1,041.25
1,677.81
Total offline spending amount (€) 1,505.21 2,825.98 3,554.61
1,718.19
Average online purchase share (%) 72.64 46.01 42.16 78.83
⁎ Significant at p b .10.
⁎ ⁎ Significant at p b .05.
⁎ ⁎ ⁎ Significant at p b .01.
73K. Campo, E. Breugelmans / Journal of Interactive Marketing
31 (2015) 63–78
only after they gain more online buying experience. To assess
the
overall effect of assortment differences, these results have to be
42. evaluated in combination with the endogeneity correction
effects.
The coefficient of the assortment control function residuals is
only significant at 10% for segment 3, indicating that there is
no serious endogeneity problem for the assortment variable
(Wooldridge 2013). Overall, these results indicate that
consumers
are sensitive to assortment differences (except for segment 4),
and
that actual differences in online and offline assortments are still
mainly guided by other managerial considerations than expected
customer reactions (no substantial endogeneity effect).
For price differences, we find a negative and significant effect
for the online grocery skeptic segment 2 (δ20,s2 = −1.564,
p b .01), and no significant effect for the other three segments.
Yet, in contrast to assortment, we obtain significant effects for
the
residual of the price correction function in all segments except
segment 1. This indicates not only that the price variable is
endogenous, but also that the online-offline price differences
are
in line with category differences in price sensitivity. This is
confirmed by the results of a model without endogeneity
correction, where price effects are negative and significant for
three out of four segments. The moderating effect of experience
is – contrary to our expectations – positive and significant for
the online grocery fan segments 1 and 4 (δ21,s1 = 1.041, p b
.01;
δ21,s4 = 1.050, p b .01) and not significant for the other two
segments. So, while the price sensitivity of the online grocery
skeptic segment 2 consumers does not change their allocation
pattern when they gain additional experience (and online price
knowledge), consumers of online grocery fan segments 1 and 4
tend to adjust their spending levels to channel price differences
in
43. an upward way (i.e., they increase the online share for
categories
with larger online price premiums).
Promotions do not lead to higher spending levels in the
category except for the new online grocery fan segment 1
74 K. Campo, E. Breugelmans / Journal of Interactive
Marketing 31 (2015) 63–78
(δ30,s1 = .737, p b .01), who may pay more attention to online
promotional stimuli than online grocery skeptics or experienced
online grocery fans. This is also in line with previous
observations that – in general – promotions predominantly
affect brand choices, and have a much smaller or no effect
on category demand and store choices (Bell, Chian, and
Padmanabhan 1999). As expected, the effect does not change
with higher levels of online buying experience as none of the
interactions with experience are significant.
Categories for which in-store stimuli are important, are
purchased less easily in online stores as indicated by the
negative and significant effect on SCS decisions in each of the
segments. For the occasional online grocery shopper segment
3, this effect does not change with higher levels of experience
(they already adapted their allocation patterns prior to the
estimation period) while experience reinforces the negative
effect for the online grocery skeptic segment 2 (δ41,s2 =
−3.092, p b .01). For online grocery fan segments 1 and 4,
the effects are only marginally significant and very small
(segment 1: δ41,s1 = −.650, p b .10; segment 4: δ41,s4 = −.367,
p b .10). Overall, experience thus appears to have a negligible
effect on the sensitivity to in-store stimuli.
In terms of the impact of transaction utility factors, the
44. results provide support for the assumption that consumers will
allocate a relatively low share of sensory category purchases to
the online store: three out of four segments have a significant
negative effect for sensory categories (δ50,s1 = −4.527, p b .01;
δ50,s2 = −3.379, p b .01; δ50,s3 = −1.695, p b .10), and not for
the experienced online grocery fan segment 4. Experience has,
as expected, a positive effect on the share of sensory purchases
allocated to the online store for online grocery fan segments 1
and 4 (δ51,s1 = 2.054, p b .01; δ51,s4 = .47, p b .05). Experi -
ence has no effect on the online share in sensory purchases for
the online grocery skeptic segment 2, and a negative reinforcing
effect for the occasional online grocery shopper segment 3
(δ51,s3 = −0.519, p b .05), possibly as a result of negative
experiences with online sensory purchases.
In line with its shopping convenience benefit, the online store
attracts a relatively larger share of bulky and heavy category
purchases for all segments (δ60,s1 = 2.118, p b .01; δ60,s2 =
5.212, p b .01; δ60,s3 = 4.156, p b .01; δ60,s4 = .681, p b .01).
In
contrast to our expectations, however, the effect weakens in
three
out of four segments (δ61,s1 = −.848, p b .01; δ61,s2 = −9.724,
p b .01; δ61,s3 = −.762, p b .01) and strengthens in the other
segment (δ61,s4 = .552, p b .01). Consumers of the experienced
online grocery fan segment 4 that were somewhat more con-
servative at the start (smaller magnitude of main effect for
bulky/
heavy) appreciate the shopping convenience benefit more and
more over time. Consumers of the other segments that were
more
convinced about the shopping convenience benefit at the start
(larger magnitude of main effect for bulky/heavy) gradually
lower the online share of bulky and heavy categories. While the
convenience effect of heavy/bulky categories remains positive
and significant for all segments, the difference in effect across
45. segments becomes smaller as consumers gain more experience
with buying these categories online, but still varies
substantially
across the four segments.
Discussion and Conclusions
The objectives of this research were twofold. First, we
wanted to provide a comprehensive analysis of the factors that
affect purchase allocation decisions of multichannel grocery
shoppers, thereby controlling for potential endogeneity bias es
in marketing mix effects. Second, we wanted to investigate the
effect of online buying experience and test whether and for
which
factors experience can have an online purchase enhancing or
rather reducing effect.
Factors of Multichannel Purchase Allocation Decisions
The results confirm that acquisition and transaction utility
based factors can influence the share of category purchases that
is
allocated to the online store. The large majority of multichannel
shoppers (65%) is less inclined to buy categories online for
which
the online store offers a less attractive (smaller) assortment.
Channel differences in price and promotion intensity have
respectively a negative and positive effect on a smaller subset
of multichannel shoppers (22% price, 29% promotion). All
consumers are less sensitive to in-store incentives and buy
substantially less impulse categories in the online channel
compared to the overall allocation of grocery purchases to the
online store. In addition to these traditional allocation factor s,
we
find significant effects of intrinsic category characteristics that
affect online transaction utility. As expected, the majority of
consumers (65%) is less inclined to buy sensory products online
46. because of the higher perceived online purchase risk and all
consumers purchase substantially more heavy/bulky products to
take advantage of online convenience benefits.
The Moderating Effect of Category-specific Online Buying
Experience
Previous research on general online purchase barriers has
stressed the positive impact of online experience in reducing
the resistance to buy online caused by factors such as the
financial risk of online transactions (Frambach, Roest, and
Krishnan 2007; Iyengar, Ansari, and Gupta 2007; Kim, Ferrin,
and Raghav Rao 2008). We observe a similar attenuating effect
of category-specific online buying experience for risk related
category characteristics. The negative effect of a lack of
sensory
information gradually disappears for about 30% of the multi -
channel shoppers (‘new online grocery fans’), when they gain
more experience with buying sensory categories online and get
accustomed to selecting these products without prior physical
inspection.
Yet, in contrast to what has been found for online buying
experience in general, we show that more experience may also
lead to adverse effects for marketing mix based differences in
acquisition utility between both channels. Given the customers'
low involvement with grocery purchases and high time pressure
during a multi-category shopping task, they are often not
prepared to engage in complex evaluations such as detailed
comparisons of online–offline assortments. Instead, consumers
gain a better insight into actual assortment differences through
75K. Campo, E. Breugelmans / Journal of Interactive Marketing
31 (2015) 63–78
47. an experience-based learning process. As a result, more than
one third of the respondents (‘online grocery skeptics’ and
‘occasional online grocery shoppers’) gradually reduce their
online purchases of categories with a smaller online assortment
in favor of the offline channel as they become more clearly
aware of the restrictions in choice variety. Channel differences
in price also have a stronger impact on allocation patterns for
some consumers when they gain experience, but in contrast to
our expectations, the interaction effect with experience is
positive (larger share of category spending for categories with a
higher online price) for ‘new’ and ‘experienced online grocery
fans’. The results of the endogeneity correction indicate that for
segment 4 (‘experienced online grocery fans’), management has
anticipated channel differences in the online willingness-to-pay
correctly (significant price residual coefficient). The results for
segment 1 (‘new online grocery fans’) suggest that these
consumers are more quality-oriented (e.g., strong positive main
effect of assortment) and not very sensitive to price (no
significant
main or endogeneity correction effect). This can explain the
lack
of a negative effect of experience on online purchase shares of
categories with a larger price difference.
As expected, we did not find any moderating effect of
experience on the reaction to channel differences in promotion
intensity which are easy to evaluate from the start and do not
require any learning and adjustment process. While we expected
a similar (non-significant) effect for impulse purchases
triggered
by in-store stimuli and online shopping convenience advantages
of heavy/bulky categories, experience has a negative effect
(marginally significant) for 51% of the consumers on impulse
purchases and 65% for heavy/bulky categories. For impulse
purchases, this can probably be explained by the fact that
consumers unfamiliar with the online grocery shopping environ-
48. ment have to search more to find the needed products which
increases their exposure to in-store stimuli. For heavy/bulky
categories, experience attenuates the allocation effect for most
consumers, but reinforces it for those who initially made less
use
of the online convenience advantage. As a result, the difference
across consumer segments becomes smaller, but the effect
remains significant and positive for all consumers.
In terms of differences across consumers, results show that
there are clear differences in how segments change allocation
patterns when gaining more experience. Segments that are
enthusiastic about online shopping and its benefits (new and
experienced online grocery fans) are more likely to show
attenuating effects that reduce category differences in purchase
allocation. Segments that use the online store less frequently
(online grocery skeptics and occasional online grocery
shoppers)
are less likely to adjust allocation over time and can even face
reinforcing effects that increase category differences in alloca -
tions when their experience level remains low.
Managerial Implications
Grocery retailers increasingly recognize the importance of
online stores to retain the existing customer base and nowadays
most of the large chains have opened an online store next to
their
traditional offline supermarkets. By offering an additional
distribution channel that complements offline stores and offers
unique benefits such as greater accessibility and more
convenience
and time saving (Chu et al. 2010; Gupta and Kim 2010), they
hope to increase their value proposition and gain a competitive
advantage over single-channel retailers (Chintagunta, Chu, and
Cebollada 2012; Kabadayi, Eyuboglu, and Thomas 2007; Zhang
49. et al. 2010). Yet, to assess and improve the profitability of the
multichannel strategy, retailers not only need to understand
whether and why customers will adopt the new online channel,
but also which share of the shopping baskets the online store
can
attract to cover its relatively high operational costs. Our
findings
contribute to a better understanding of the factors underlying
category differences in online performance and may in this way
help to define appropriate promotional and corrective actions
that
can be taken to stimulate online purchases of less successful
categories.
A first important insight that can be derived from our
findings is that different actions may be needed to stimulate
online purchases. For marketing mix related factors, retailers
should realize that multichannel shoppers may react negatively
to excessive online assortment reductions, especially when they
gain more online buying experience. Large assortment
reductions can then have an important negative effect, implying
that online retailers may have to invest in upgrading online
assortments to better match the offline product offer. Online
shoppers are, on the other hand, more willing to tolerate online
price premiums when they gain more online buying experience
(and are thus better able to appreciate the online shopping
advantages). Nevertheless, for a substantial segment of con-
sumers (about 22%), high online price premiums do
significantly
reduce the attractiveness of the online offer. While experience
does not reinforce this effect as we expected, it does not
attenuate
it either.
The lower sensitivity to in-store incentives in the online
environment calls for promotional tactics that are better tailored
50. to the specific online environment, e.g., personalized
promotions,
cross-selling opportunities, tailored in-store displays (Bellman
et al. 2013; Breugelmans and Campo 2011; Punj 2011) and that
may stimulate purchases of impulse categories in the online
channel. In addition, marketing communication can play an
important role in reducing the perceived risk and uncertainty of
online purchases and help customers to adjust decision rules to
the new shopping environment (Weathers, Sharma, and Wood
2007). Retailers can, for instance, use customer reviews or other
electronic word-of-mouth to highlight the positive experiences
of
other shoppers with buying sensory categories online (Jiménez
and Mendoza 2013; Purnawirawan, De Pelsmacker, and Dens
2012). They can also help consumers by providing substitute
information cues (such as expiration dates and quality labels)
and by clarifying their usefulness in judging the product quality
of sensory categories. Lastly, retailers can stress the online
convenience benefits in their marketing communications to
further spur the higher tendency of buying heavy/bulky products
in the online channel.
A second important finding is that experience can have a
positive as well as a negative effect on the tendency to allocate
purchases of specific categories to the online channel. Results
76 K. Campo, E. Breugelmans / Journal of Interactive
Marketing 31 (2015) 63–78
show, for instance, that an increase in experience can strengthen
the negative effect of assortment differences. This points to
potential limitations for retailers when using assortment
signaling
strategies. While less visible assortment reductions (eliminating
less popular items) may initially mask the less attractive online
51. offer, increased experience with buying the categories online
may
improve the customer's assortment knowledge and may result in
a stronger negative effect on online category allocations. On the
other hand, experience may reduce the perceived risk of buying
sensory categories online and thereby enhance online purchases
of these categories. Hence, retailers should strive to enhance
positive experiences by stimulating trial and repeat purchases
for
sensory categories as it offers opportunities to reduce online
purchase risk.
Lastly, our findings indicate that there are clear differences
in how segments adjust their allocation pattern as they gain
more online buying experience. For the segment of frequent
online buyers, who are also more willing and open to buy
several types of categories in the online store, special loyalty
programs could be developed to maintain and reinforce their
use of the online channel. For the group of customers that spend
a smaller share of grocery products in the online channel and
who limit their online purchases to a more restrictive, ‘safer’
set
of categories, extension of online purchases could be aimed for,
for instance, by stimulating trial purchases of categories with a
higher perceived online buying risk (e.g., sensory categories).
In
this way, these consumers experience (free or with promotion)
the positive outcomes of more risky purchases in the online
channel, which may help in developing trust in the multichannel
retailer's ability to provide a high-quality online service (Urban,
Amyx, and Lorenzon 2009).
Directions for Further Research
Although our study provides interesting new insights into the
effect of multichannel category allocation factors and the
52. moderating effect of category-specific online buying
experience,
it also has important limitations and points to several
interesting
areas for additional research. For one, more refined definitions
of
the category allocation factors could help to obtain a better
insight
into their effect on online buying behavior. For instance, a
focus
on assortment composition in addition to size may lead to
additional and more refined insights. Likewise, using a
household-
specific rating of impulsiveness (rather than assuming it is a
characteristic that is constant across consumers) or allowing
price
and assortment to vary over time are important refinements that
are worthwhile to investigate in more depth. Second, it would
be
valuable to obtain an in-depth insight into experience effects
and
how they work, exploring their impact on mediating variables
such as learning processes and online retailer trust. Third,
an interesting extension of our study would be to explore
cross-category effects, such as the potential weakening effect of
buying one sensory category as experience reduction for another
sensory category, or the accumulated negative effect of encoun-
tering a large number of categories with price and assortment
disadvantages. Fourth, because of data availability, the focus of
this paper is on consumers' shopping behavior in a single chain
multichannel grocery context. While this approach has the
advantage of eliminating confounding effects of differences in
assortment composition and retail strategy across different
grocery
chains, for instance and although previous research has demon-
strated that the large majority of multichannel shoppers visit the
53. same chain in the online and offline channel (Melis et al. 2013),
a
more detailed and complete analysis could be carried out if data
of
competitive chains would also be available. This would allow
for a
simultaneous analysis of category allocation decisions over
different channels and chains providing a more complete picture
of the complex competitive relationships in a multichain
multichannel retail context. Finally, examining the impact of
category allocation decisions in a non-grocery shopping context
(where characteristics like perishability overlap less with
sensory
characteristics) could offer a useful and interesting extension.
Acknowledgments
The authors thank the online grocery retailer who provided
the data used in this study, and Huiying He and Kim Goeleven
for their help. They further thank Koert van Ittersum, Siegfried
Dewitte, Vera Blazevic and Lien Lamey for their helpful
suggestions on previous versions of this article.
Appendix A. Supplementary Data
Supplementary data to this article can be found online at
http://dx.doi.org/10.1016/j.intmar.2015.04.001.
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