- The document analyzes consumers' consideration towards purchasing electrical appliances with energy labels in Hong Kong.
- It aims to understand the relationship between green perceived value, green perceived risk, green trust and green purchase intention.
- The study found that green perceived value positively influences green trust and purchase intention, while green perceived risk negatively influences green trust and purchase intention. Green trust also positively influences purchase intention.
This document discusses key findings from Food Processing's 2012 Manufacturing Trends Survey. Some of the main points include:
- Food safety and cost control remained the top two manufacturing priorities for food and beverage processors in 2012. Food safety garnered 53% of first place votes.
- Processors remain cautiously optimistic about 2012 prospects despite economic uncertainty and challenges like rising costs. 45% said their companies were growing in 2012.
- The article then discusses three trends that will redefine the food and beverage industry over the next decade: a focus on sustainability from both consumers and manufacturers, the growing impact of technology on food purchases, and changing demographics and the new expectations that come with them.
Republic of Ireland Faculty RCGP Winter meeting December 2017 William BehanDrWilliamBehan
This document discusses healthcare funding and general practice in Ireland. It begins by outlining the "Triple Aim" of enhancing patient experience, improving population health, and reducing costs. It then discusses how burnout among providers can undermine this aim and proposes a "Quadruple Aim" of also caring for providers. The document presents international evidence that increased primary care and general practice is associated with better outcomes and lower costs. It also shows data on accessibility of care in Ireland and trends in healthcare spending.
This document presents a study that explores the relationships between consumption atmosphere, word-of-mouth, perceived value, and behavioral intention. The study aims to understand how these factors influence customer decision-making. It develops five research questions and hypotheses to test the relationships between the variables. The methodology section describes a questionnaire that will be used to survey customers at various restaurants. Statistical analysis including regression analysis and ANOVA will then be used to analyze the data and test the hypotheses. The goal is to provide useful insights for marketing in the hospitality industry.
Genichi Taguchi was a Japanese engineer known for developing quality engineering and loss function methodologies. He developed statistical methods to improve product quality and reduce costs, including quality loss functions and orthogonal arrays. Quality loss functions graphically depict how deviations from a target value result in losses, with losses increasing quadratically as deviation increases. This approach aims to minimize total losses by reducing variability from the target. Orthogonal arrays are experimental designs that allow investigation of many factors using few experimental runs. Taguchi's work aims to improve quality without increasing costs by reducing variability from targets.
A study on customer satisfaction level on green products with special referen...Dr. Linda Mary Simon
- The document summarizes a study on customer satisfaction with green products in Coimbatore district, India.
- It conducted a survey of 100 customers to assess their awareness and satisfaction with green products, willingness to purchase them, and willingness to pay more for them.
- The results found that 56% of customers were satisfied with green products they had used, 66% were aware of green products, 51% were willing to try green products always and 48% sometimes, 42% were willing to pay more always and 53% sometimes.
- Statistical tests like the Kolmogorov-Smirnov test were used to validate the data and determine appropriate tests for analysis.
This study aims to assess the factors influencing the green behavior of faculty and staff at Mindanao State University - Iligan Institute of Technology. It will examine the relationship between green behavioral control, green product trust, green product value, green environmental awareness, green price sensitivity, and green behavior. A survey will be conducted to collect data on respondents' demographic profiles and factors affecting green behavior. Statistical analysis using SmartPLS will be performed to measure construct validity and reliability, and examine the relationships between variables. This will determine the most and least influential factors on respondents' green behavior.
The document summarizes a research study that examined factors influencing Chinese consumers' attitudes and purchase intentions towards green products. The study found that:
1) Environmental concerns, beliefs about the effectiveness of green products, and perceptions of green products' functional benefits positively influence consumers' attitudes.
2) Consumers' attitudes partially or fully mediate the influence of these factors on purchase intentions.
3) Awareness of government policy did not significantly impact attitudes or purchase intentions.
The study provides insights but has limitations due to its sample and geographic scope. Future research could explore attitudes across more cities and demographics and consider the impacts of knowledge and specific price levels.
The aim of the study that consumer‟s perception towards green products relates to its health aspects. The present study shows that consumers are having more conscious about health so they are willing to purchase the green products. The research findings of this study implies that should environmental consciousness , product quality, no preservatives, health conscious and price of green products will make consumers will be more likely to have purchase behavior of green products. Consumers in Madurai are highly concerned about the environment should be the first target segment for green product marketers. When consumers get health conscious and awareness about green products is positive they display higher concern for environment and probably make more steps to reduce the impact of environment.
This document discusses key findings from Food Processing's 2012 Manufacturing Trends Survey. Some of the main points include:
- Food safety and cost control remained the top two manufacturing priorities for food and beverage processors in 2012. Food safety garnered 53% of first place votes.
- Processors remain cautiously optimistic about 2012 prospects despite economic uncertainty and challenges like rising costs. 45% said their companies were growing in 2012.
- The article then discusses three trends that will redefine the food and beverage industry over the next decade: a focus on sustainability from both consumers and manufacturers, the growing impact of technology on food purchases, and changing demographics and the new expectations that come with them.
Republic of Ireland Faculty RCGP Winter meeting December 2017 William BehanDrWilliamBehan
This document discusses healthcare funding and general practice in Ireland. It begins by outlining the "Triple Aim" of enhancing patient experience, improving population health, and reducing costs. It then discusses how burnout among providers can undermine this aim and proposes a "Quadruple Aim" of also caring for providers. The document presents international evidence that increased primary care and general practice is associated with better outcomes and lower costs. It also shows data on accessibility of care in Ireland and trends in healthcare spending.
This document presents a study that explores the relationships between consumption atmosphere, word-of-mouth, perceived value, and behavioral intention. The study aims to understand how these factors influence customer decision-making. It develops five research questions and hypotheses to test the relationships between the variables. The methodology section describes a questionnaire that will be used to survey customers at various restaurants. Statistical analysis including regression analysis and ANOVA will then be used to analyze the data and test the hypotheses. The goal is to provide useful insights for marketing in the hospitality industry.
Genichi Taguchi was a Japanese engineer known for developing quality engineering and loss function methodologies. He developed statistical methods to improve product quality and reduce costs, including quality loss functions and orthogonal arrays. Quality loss functions graphically depict how deviations from a target value result in losses, with losses increasing quadratically as deviation increases. This approach aims to minimize total losses by reducing variability from the target. Orthogonal arrays are experimental designs that allow investigation of many factors using few experimental runs. Taguchi's work aims to improve quality without increasing costs by reducing variability from targets.
A study on customer satisfaction level on green products with special referen...Dr. Linda Mary Simon
- The document summarizes a study on customer satisfaction with green products in Coimbatore district, India.
- It conducted a survey of 100 customers to assess their awareness and satisfaction with green products, willingness to purchase them, and willingness to pay more for them.
- The results found that 56% of customers were satisfied with green products they had used, 66% were aware of green products, 51% were willing to try green products always and 48% sometimes, 42% were willing to pay more always and 53% sometimes.
- Statistical tests like the Kolmogorov-Smirnov test were used to validate the data and determine appropriate tests for analysis.
This study aims to assess the factors influencing the green behavior of faculty and staff at Mindanao State University - Iligan Institute of Technology. It will examine the relationship between green behavioral control, green product trust, green product value, green environmental awareness, green price sensitivity, and green behavior. A survey will be conducted to collect data on respondents' demographic profiles and factors affecting green behavior. Statistical analysis using SmartPLS will be performed to measure construct validity and reliability, and examine the relationships between variables. This will determine the most and least influential factors on respondents' green behavior.
The document summarizes a research study that examined factors influencing Chinese consumers' attitudes and purchase intentions towards green products. The study found that:
1) Environmental concerns, beliefs about the effectiveness of green products, and perceptions of green products' functional benefits positively influence consumers' attitudes.
2) Consumers' attitudes partially or fully mediate the influence of these factors on purchase intentions.
3) Awareness of government policy did not significantly impact attitudes or purchase intentions.
The study provides insights but has limitations due to its sample and geographic scope. Future research could explore attitudes across more cities and demographics and consider the impacts of knowledge and specific price levels.
The aim of the study that consumer‟s perception towards green products relates to its health aspects. The present study shows that consumers are having more conscious about health so they are willing to purchase the green products. The research findings of this study implies that should environmental consciousness , product quality, no preservatives, health conscious and price of green products will make consumers will be more likely to have purchase behavior of green products. Consumers in Madurai are highly concerned about the environment should be the first target segment for green product marketers. When consumers get health conscious and awareness about green products is positive they display higher concern for environment and probably make more steps to reduce the impact of environment.
An Exploration Study On Factors Influencing Green MarketingApril Smith
This document presents the results of a factor analysis on factors influencing green marketing. The analysis identified 4 key factors:
1) Green labeling - including simplicity of labels, understandability, sufficient information, and relevance of information.
2) Compatibility - including important label information, building customer relationships, recyclability, trust, and packaging.
3) Product value - including attractiveness, visibility, suitability, and reasons for higher prices.
4) Advertising components - including five unnamed factors related to green advertisements.
The factor analysis was conducted on survey responses from 200 people visiting an organic product exhibition.
The document summarizes a study examining consumer preferences for green recyclable products. It identifies 12 variables that may affect consumer purchasing behavior. A questionnaire using a Likert scale was designed to measure attitudes on 9 of the variables. Discriminant analysis was used to analyze the data and differentiate consumers into two groups: buyers or non-buyers of green products based on the factors. The analysis identified key variables that influence whether a consumer purchases green recyclable products.
Green marketing refers to the process of selling products and/or services based on their environmental benefits. Such a product or service may be environmentally friendly in itself or produced and/or packaged in this way.
This study explores the gap between attitudes and behaviors regarding the purchase of voluntary carbon offsets by Australian consumers. The researchers conducted a survey of 83 respondents to test four hypotheses: 1) There is a gap between positive climate change attitudes and actual purchases. 2) Attitudes predict purchase intentions. 3) Purchases are low due to lack of knowledge. 4) Purchases are difficult. The results supported all hypotheses, finding an attitude-behavior gap, a relationship between attitudes and intentions, lower knowledge among non-purchasers, and perceptions of difficulty. The study contributes to understanding how to increase knowledge and access to encourage more pro-environmental behavior.
This report summarizes research conducted for Poly-Wood, Inc. to better understand consumers of outdoor furniture made from recycled materials. The research had two objectives: 1) to identify the demographics of those who purchase such furniture and compare to Poly-Wood customers, and 2) to understand the importance of various factors in the purchasing decision. The methods included a literature review and survey of 676 participants. Results showed that the target demographic is women ages 46-65 with an income of $75,000-$149,000 who are more aware of brands like Poly-Wood. Price is less important to those seeking recycled materials. It is recommended that Poly-Wood target their identified demographic and emphasize appearance in marketing.
- The document discusses a research project on green branding in the IT industry.
- It aims to identify functional and emotional attributes that help create an effective green brand positioning strategy for IT products.
- The research methodology involves a descriptive research design using a survey questionnaire to understand consumer perceptions of various green branding strategies employed by IT companies.
This document summarizes a study on factors influencing green purchase intentions among Pakistani consumers. The study found that organizational green image, environmental concern, environmental knowledge, and perceived product price and quality positively influence consumers' green purchase intentions. It also found that perceived product price and quality moderate the effects of organizational green image, environmental concern, and environmental knowledge on purchase intentions. The study utilized a survey of 377 Pakistani university students and established several hypotheses about the relationships between variables that were all supported by the results. However, it notes limitations including the sample only representing students and not measuring actual purchasing behavior.
Market research on green technology consumers, including a "greenovator" segmentation and interest in green technology. Presented by Joe Bates, Charles Colby and Joe Taliuaga at the Frontiers in Services Conference, 2008.
This document discusses determining the high value information needed to improve decisions around development interventions. It focuses on four strategic objectives: decreasing food insecurity, managing environmental resources, reducing poverty among farmers, and increasing nutrition, health and wellbeing. The document outlines challenges like quantifying uncertainty, measuring outcomes, and showing the value of research. It also discusses using applied information economics to identify key metrics, quantify information value, and improve intervention design and impacts. The overall goal is to develop systems for measuring and analyzing impacts and tradeoffs to help stakeholders make better policies and intervention decisions.
The document presents CompTool, POLYGEN's product comparison platform that provides quantitative environmental impact data and analytics to empower informed consumer and business decisions. It provides screenshots of CompTool's interface and analytics capabilities. POLYGEN's business strategy involves partnering with retailers to build out CompTool's database and marketing the tool through direct sales and affiliates
This project tells about the customer of our market how they will buy green products and how they will make decision while purchasing a green product. Eco-friendly good are more welcomed by customers who are environmentally responsible. It tells what factor are affecting green behavior and decision making of customers. The basic objective of this project is how consumer will make its green purchase decision and behavior toward green products. By the analysis of asking questions to businessmen, jobholder and students found that there is strong positive relationship between consumer green behavior and price, quality and green marketing while brand and gender difference has very weak relationship with consumer green behavior. These results will be helping for the managerial implications. Industries can use this for future strategies and get know how about the customer intention to buy green products. And it will also tell that what is more important near to customer about green products.
This study examined factors that influence green purchase intentions in Pakistan. It hypothesized that organizational green image, environmental concern, environmental knowledge, and perceived product price and quality positively influence green purchase intentions. Data was collected through surveys of 377 university students. Correlation and regression analyses found support for all hypotheses, showing these factors have significant positive relationships with green purchase intentions. Additionally, perceived price and quality was found to moderate the influence of organizational green image, environmental concern, and environmental knowledge on green purchase intentions. The study concludes price and quality competitiveness is important for driving green purchase intentions, especially among educated consumers.
2017 Top Energy Reduction Tactics Webinar slidesLucid
The document summarizes the results of two sustainability surveys conducted in 2017. It finds that 90% of organizations remain committed to or are increasing sustainability commitments. 50% have formal climate or sustainability targets, with business performance and ROI influencing 75% of energy projects. The top metrics for tracking program success are energy consumption, cost, and emissions. Building upgrades, measurement/tracking, and scheduling improvements were prioritized. Over the past year, successes came from upgrades, measurement, scheduling, and engagement. The webinar agenda included reviewing these survey findings and initiatives, as well as a panel on formal/informal commitments and top energy reduction tactics.
STATISTICAL ANALYSIS ON CONSUMER’S PERCEPTION TOWARDS CONSUMPTION OF GREEN PR...IAEME Publication
Global environmental problems are growing day-by-day and the concern about
environmental problems is also given importance by everybody. All environmental
problems are generated by human-beings. So, there is great need to identify the
consumers’ perception towards green products available in the society. The present
study was an attempt to have insights of the consumers’ perception towards the
consumption of green products using percentage analysis and ANOVA. The study
helps the entrepreneurs to understand the perception of the consumer and formulate
their strategies based on it. It further helps to sensitize the people towards
environmental issues and help them modify their behaviour accordingly to consume
green products and save the earth. A sample of 250 consumers who were using green
products has been covered in the study and the results were highlighted using
diagrams and tables.
Environmental Issues in Business 2011Environmental Issues .docxYASHU40
Environmental Issues in Business 201
1
Environmental Issues in Business 201
Time (Stress) ManagementWeek 2Become familiar with topics Week 3Preliminary literature review Week 4Topic selection & literature review Week 5 (Tuition free week)Literature review and early draft stage Week 6Advancing manuscript Week 7Advancing manuscript Week 8 (Tuition free week)Finalising manuscript Week 9Proof-reading and checkingWeek 10Paper submission due
Lecture 8
Green Marketing
Environmental Issues in Business 201
3
At the end of this lecture you will be able to:
explain the role of green marketing in the sustainability context;
describe differences between green marketing and conventional marketing approaches;
describe the strengths and weaknesses of green marketing; and
identify key elements of effective green marketing.
The marketing paradox
How do marketing and sustainability fit together?
Schism in the marketing discipline
Genuinely green vs greenwashing
Greener vs sustainable marketing
The problem of marketing “greenness”
How green can be too green
Consumers as green marketing obstacles
Designing a green marketing strategy
The dos and don’ts
Examples
The good, bad and ugly
Environmental Issues in Business 201
4
Overview
Lecture 7
Environmental Issues in Business 201
4
How well does marketing align with the goals of sustainable development?
Environmental Issues in Business 201
5
The paradox of marketing:
Marketing is the driving force behind unsustainable, (un-)economic growth and individual lifestyles
Contributes to over-consumption
Complicit in the promotion of unsustainable/unethical values and behaviours
Environmental Issues in Business 201
6
How Responsible is Marketing?
The ‘more is better maxim’ of marketing seems to violate sustainability principles and arguably undermines efforts to mainstream more ethical and ecologically sensitive consumer behaviour
Lecture 7
Environmental Issues in Business 201
6
Sustainable production and consumption.
But can also be used as a tool for social change:
Altering consumption patterns for society’s long-term best interests
Educate and raise awareness
Change values, life-styles and consumer choice
Help challenge the status quo
Environmental Issues in Business 201
7
Marketing: A Tool for Change?
Promotion of products or services by employing environmental claims either about their attributes or about the systems, policies and processes of the firms that manufacture or sell them
(Prakash 2002: 285)
Channelling of consumer demand towards environmentally less problematic areas of consumption
(Hockerts 2003)
Environmental Issues in Business 201
8
Green Marketing
Product attributes
Value-addition processes
Management systems
Associated Causes
Environmental Issues in Business 201
9
Target Areas for Green Marketing
Source: Prakash (2002)
Green marketing can help:
Aid reduction of impacts
Provide alternative product choices
Promote ‘better’ ...
Refinitiv enables tailored integration of ESG into the research, investment vehicle creation, and investment management processes through audible, standardized data across all Environmental, Social and Governance pillars, transparent and customizable rating mechanism, and regularly updating controversies. Refinitiv provides a wide range of concorded historic and forward looking fundamental and pricing data, and value-add index calculation services supporting thematic investments. Refinitiv aims to be the next step in ESG Integration.
Getting Buy-in: Marketing and Communications as a tool for Engagement and Beh...Ksenia Benifand
As organizations work to align their branding and marketing efforts with their Corporate Social Responsibility (CSR) and sustainability commitments, they are now more than ever looking to engage customers in choosing more sustainable products and services. However, although a vast majority of consumers are enthusiastic about the green movement, they lack the same enthusiasm when it comes to actually spending money and making meaningful adjustments to lifestyle choices.
This presentation explores marketing and advertising as a tool to effectively engage consumers by looking at how we make decisions and exploring our most prevailing and unique world views.
These tools can be applied to a variety of marketing and communication contexts to create messages that overcome “green fatigue”, inspire sustainable behaviour change, and enhance customer loyalty.
The document summarizes a study on consumers' perceptions of green products in India. It found that while most consumers have purchased green products, only 15% do so regularly. It segmented consumers into light green and dark green based on purchase frequency. Dark green consumers care more about product ingredients and are older, more educated and affluent than light green consumers. Both segments cite environmental benefits but light green consumers also consider cost and satisfaction. The study provides recommendations for marketers on segmentation, messaging and pricing to better target both groups.
We will explore the transformative journey of American Bath Group as they transitioned from a traditional monolithic CMS to a dynamic, composable martech framework using Kontent.ai. Discover the strategic decisions, challenges, and key benefits realized through adopting a headless CMS approach. Learn how composable business models empower marketers with flexibility, speed, and integration capabilities, ultimately enhancing digital experiences and operational efficiency. This session is essential for marketers looking to understand the practical impacts and advantages of composable technology in today's digital landscape. Join us to gain valuable insights and actionable takeaways from a real-world implementation that redefines the boundaries of marketing technology.
Mastering Local SEO for Service Businesses in the AI Era"" is tailored specifically for local service providers like plumbers, dentists, and others seeking to dominate their local search landscape. This session delves into leveraging AI advancements to enhance your online visibility and search rankings through the Content Factory model, designed for creating high-impact, SEO-driven content. Discover the Dollar-a-Day advertising strategy, a cost-effective approach to boost your local SEO efforts and attract more customers with minimal investment. Gain practical insights on optimizing your online presence to meet the specific needs of local service seekers, ensuring your business not only appears but stands out in local searches. This concise, action-oriented workshop is your roadmap to navigating the complexities of digital marketing in the AI age, driving more leads, conversions, and ultimately, success for your local service business.
Key Takeaways:
Embrace AI for Local SEO: Learn to harness the power of AI technologies to optimize your website and content for local search. Understand the pivotal role AI plays in analyzing search trends and consumer behavior, enabling you to tailor your SEO strategies to meet the specific demands of your target local audience. Leverage the Content Factory Model: Discover the step-by-step process of creating SEO-optimized content at scale. This approach ensures a steady stream of high-quality content that engages local customers and boosts your search rankings. Get an action guide on implementing this model, complete with templates and scheduling strategies to maintain a consistent online presence. Maximize ROI with Dollar-a-Day Advertising: Dive into the cost-effective Dollar-a-Day advertising strategy that amplifies your visibility in local searches without breaking the bank. Learn how to strategically allocate your budget across platforms to target potential local customers effectively. The session includes an action guide on setting up, monitoring, and optimizing your ad campaigns to ensure maximum impact with minimal investment.
An Exploration Study On Factors Influencing Green MarketingApril Smith
This document presents the results of a factor analysis on factors influencing green marketing. The analysis identified 4 key factors:
1) Green labeling - including simplicity of labels, understandability, sufficient information, and relevance of information.
2) Compatibility - including important label information, building customer relationships, recyclability, trust, and packaging.
3) Product value - including attractiveness, visibility, suitability, and reasons for higher prices.
4) Advertising components - including five unnamed factors related to green advertisements.
The factor analysis was conducted on survey responses from 200 people visiting an organic product exhibition.
The document summarizes a study examining consumer preferences for green recyclable products. It identifies 12 variables that may affect consumer purchasing behavior. A questionnaire using a Likert scale was designed to measure attitudes on 9 of the variables. Discriminant analysis was used to analyze the data and differentiate consumers into two groups: buyers or non-buyers of green products based on the factors. The analysis identified key variables that influence whether a consumer purchases green recyclable products.
Green marketing refers to the process of selling products and/or services based on their environmental benefits. Such a product or service may be environmentally friendly in itself or produced and/or packaged in this way.
This study explores the gap between attitudes and behaviors regarding the purchase of voluntary carbon offsets by Australian consumers. The researchers conducted a survey of 83 respondents to test four hypotheses: 1) There is a gap between positive climate change attitudes and actual purchases. 2) Attitudes predict purchase intentions. 3) Purchases are low due to lack of knowledge. 4) Purchases are difficult. The results supported all hypotheses, finding an attitude-behavior gap, a relationship between attitudes and intentions, lower knowledge among non-purchasers, and perceptions of difficulty. The study contributes to understanding how to increase knowledge and access to encourage more pro-environmental behavior.
This report summarizes research conducted for Poly-Wood, Inc. to better understand consumers of outdoor furniture made from recycled materials. The research had two objectives: 1) to identify the demographics of those who purchase such furniture and compare to Poly-Wood customers, and 2) to understand the importance of various factors in the purchasing decision. The methods included a literature review and survey of 676 participants. Results showed that the target demographic is women ages 46-65 with an income of $75,000-$149,000 who are more aware of brands like Poly-Wood. Price is less important to those seeking recycled materials. It is recommended that Poly-Wood target their identified demographic and emphasize appearance in marketing.
- The document discusses a research project on green branding in the IT industry.
- It aims to identify functional and emotional attributes that help create an effective green brand positioning strategy for IT products.
- The research methodology involves a descriptive research design using a survey questionnaire to understand consumer perceptions of various green branding strategies employed by IT companies.
This document summarizes a study on factors influencing green purchase intentions among Pakistani consumers. The study found that organizational green image, environmental concern, environmental knowledge, and perceived product price and quality positively influence consumers' green purchase intentions. It also found that perceived product price and quality moderate the effects of organizational green image, environmental concern, and environmental knowledge on purchase intentions. The study utilized a survey of 377 Pakistani university students and established several hypotheses about the relationships between variables that were all supported by the results. However, it notes limitations including the sample only representing students and not measuring actual purchasing behavior.
Market research on green technology consumers, including a "greenovator" segmentation and interest in green technology. Presented by Joe Bates, Charles Colby and Joe Taliuaga at the Frontiers in Services Conference, 2008.
This document discusses determining the high value information needed to improve decisions around development interventions. It focuses on four strategic objectives: decreasing food insecurity, managing environmental resources, reducing poverty among farmers, and increasing nutrition, health and wellbeing. The document outlines challenges like quantifying uncertainty, measuring outcomes, and showing the value of research. It also discusses using applied information economics to identify key metrics, quantify information value, and improve intervention design and impacts. The overall goal is to develop systems for measuring and analyzing impacts and tradeoffs to help stakeholders make better policies and intervention decisions.
The document presents CompTool, POLYGEN's product comparison platform that provides quantitative environmental impact data and analytics to empower informed consumer and business decisions. It provides screenshots of CompTool's interface and analytics capabilities. POLYGEN's business strategy involves partnering with retailers to build out CompTool's database and marketing the tool through direct sales and affiliates
This project tells about the customer of our market how they will buy green products and how they will make decision while purchasing a green product. Eco-friendly good are more welcomed by customers who are environmentally responsible. It tells what factor are affecting green behavior and decision making of customers. The basic objective of this project is how consumer will make its green purchase decision and behavior toward green products. By the analysis of asking questions to businessmen, jobholder and students found that there is strong positive relationship between consumer green behavior and price, quality and green marketing while brand and gender difference has very weak relationship with consumer green behavior. These results will be helping for the managerial implications. Industries can use this for future strategies and get know how about the customer intention to buy green products. And it will also tell that what is more important near to customer about green products.
This study examined factors that influence green purchase intentions in Pakistan. It hypothesized that organizational green image, environmental concern, environmental knowledge, and perceived product price and quality positively influence green purchase intentions. Data was collected through surveys of 377 university students. Correlation and regression analyses found support for all hypotheses, showing these factors have significant positive relationships with green purchase intentions. Additionally, perceived price and quality was found to moderate the influence of organizational green image, environmental concern, and environmental knowledge on green purchase intentions. The study concludes price and quality competitiveness is important for driving green purchase intentions, especially among educated consumers.
2017 Top Energy Reduction Tactics Webinar slidesLucid
The document summarizes the results of two sustainability surveys conducted in 2017. It finds that 90% of organizations remain committed to or are increasing sustainability commitments. 50% have formal climate or sustainability targets, with business performance and ROI influencing 75% of energy projects. The top metrics for tracking program success are energy consumption, cost, and emissions. Building upgrades, measurement/tracking, and scheduling improvements were prioritized. Over the past year, successes came from upgrades, measurement, scheduling, and engagement. The webinar agenda included reviewing these survey findings and initiatives, as well as a panel on formal/informal commitments and top energy reduction tactics.
STATISTICAL ANALYSIS ON CONSUMER’S PERCEPTION TOWARDS CONSUMPTION OF GREEN PR...IAEME Publication
Global environmental problems are growing day-by-day and the concern about
environmental problems is also given importance by everybody. All environmental
problems are generated by human-beings. So, there is great need to identify the
consumers’ perception towards green products available in the society. The present
study was an attempt to have insights of the consumers’ perception towards the
consumption of green products using percentage analysis and ANOVA. The study
helps the entrepreneurs to understand the perception of the consumer and formulate
their strategies based on it. It further helps to sensitize the people towards
environmental issues and help them modify their behaviour accordingly to consume
green products and save the earth. A sample of 250 consumers who were using green
products has been covered in the study and the results were highlighted using
diagrams and tables.
Environmental Issues in Business 2011Environmental Issues .docxYASHU40
Environmental Issues in Business 201
1
Environmental Issues in Business 201
Time (Stress) ManagementWeek 2Become familiar with topics Week 3Preliminary literature review Week 4Topic selection & literature review Week 5 (Tuition free week)Literature review and early draft stage Week 6Advancing manuscript Week 7Advancing manuscript Week 8 (Tuition free week)Finalising manuscript Week 9Proof-reading and checkingWeek 10Paper submission due
Lecture 8
Green Marketing
Environmental Issues in Business 201
3
At the end of this lecture you will be able to:
explain the role of green marketing in the sustainability context;
describe differences between green marketing and conventional marketing approaches;
describe the strengths and weaknesses of green marketing; and
identify key elements of effective green marketing.
The marketing paradox
How do marketing and sustainability fit together?
Schism in the marketing discipline
Genuinely green vs greenwashing
Greener vs sustainable marketing
The problem of marketing “greenness”
How green can be too green
Consumers as green marketing obstacles
Designing a green marketing strategy
The dos and don’ts
Examples
The good, bad and ugly
Environmental Issues in Business 201
4
Overview
Lecture 7
Environmental Issues in Business 201
4
How well does marketing align with the goals of sustainable development?
Environmental Issues in Business 201
5
The paradox of marketing:
Marketing is the driving force behind unsustainable, (un-)economic growth and individual lifestyles
Contributes to over-consumption
Complicit in the promotion of unsustainable/unethical values and behaviours
Environmental Issues in Business 201
6
How Responsible is Marketing?
The ‘more is better maxim’ of marketing seems to violate sustainability principles and arguably undermines efforts to mainstream more ethical and ecologically sensitive consumer behaviour
Lecture 7
Environmental Issues in Business 201
6
Sustainable production and consumption.
But can also be used as a tool for social change:
Altering consumption patterns for society’s long-term best interests
Educate and raise awareness
Change values, life-styles and consumer choice
Help challenge the status quo
Environmental Issues in Business 201
7
Marketing: A Tool for Change?
Promotion of products or services by employing environmental claims either about their attributes or about the systems, policies and processes of the firms that manufacture or sell them
(Prakash 2002: 285)
Channelling of consumer demand towards environmentally less problematic areas of consumption
(Hockerts 2003)
Environmental Issues in Business 201
8
Green Marketing
Product attributes
Value-addition processes
Management systems
Associated Causes
Environmental Issues in Business 201
9
Target Areas for Green Marketing
Source: Prakash (2002)
Green marketing can help:
Aid reduction of impacts
Provide alternative product choices
Promote ‘better’ ...
Refinitiv enables tailored integration of ESG into the research, investment vehicle creation, and investment management processes through audible, standardized data across all Environmental, Social and Governance pillars, transparent and customizable rating mechanism, and regularly updating controversies. Refinitiv provides a wide range of concorded historic and forward looking fundamental and pricing data, and value-add index calculation services supporting thematic investments. Refinitiv aims to be the next step in ESG Integration.
Getting Buy-in: Marketing and Communications as a tool for Engagement and Beh...Ksenia Benifand
As organizations work to align their branding and marketing efforts with their Corporate Social Responsibility (CSR) and sustainability commitments, they are now more than ever looking to engage customers in choosing more sustainable products and services. However, although a vast majority of consumers are enthusiastic about the green movement, they lack the same enthusiasm when it comes to actually spending money and making meaningful adjustments to lifestyle choices.
This presentation explores marketing and advertising as a tool to effectively engage consumers by looking at how we make decisions and exploring our most prevailing and unique world views.
These tools can be applied to a variety of marketing and communication contexts to create messages that overcome “green fatigue”, inspire sustainable behaviour change, and enhance customer loyalty.
The document summarizes a study on consumers' perceptions of green products in India. It found that while most consumers have purchased green products, only 15% do so regularly. It segmented consumers into light green and dark green based on purchase frequency. Dark green consumers care more about product ingredients and are older, more educated and affluent than light green consumers. Both segments cite environmental benefits but light green consumers also consider cost and satisfaction. The study provides recommendations for marketers on segmentation, messaging and pricing to better target both groups.
Similar to (Mr)class a02b group7_presentationppt (20)
We will explore the transformative journey of American Bath Group as they transitioned from a traditional monolithic CMS to a dynamic, composable martech framework using Kontent.ai. Discover the strategic decisions, challenges, and key benefits realized through adopting a headless CMS approach. Learn how composable business models empower marketers with flexibility, speed, and integration capabilities, ultimately enhancing digital experiences and operational efficiency. This session is essential for marketers looking to understand the practical impacts and advantages of composable technology in today's digital landscape. Join us to gain valuable insights and actionable takeaways from a real-world implementation that redefines the boundaries of marketing technology.
Mastering Local SEO for Service Businesses in the AI Era"" is tailored specifically for local service providers like plumbers, dentists, and others seeking to dominate their local search landscape. This session delves into leveraging AI advancements to enhance your online visibility and search rankings through the Content Factory model, designed for creating high-impact, SEO-driven content. Discover the Dollar-a-Day advertising strategy, a cost-effective approach to boost your local SEO efforts and attract more customers with minimal investment. Gain practical insights on optimizing your online presence to meet the specific needs of local service seekers, ensuring your business not only appears but stands out in local searches. This concise, action-oriented workshop is your roadmap to navigating the complexities of digital marketing in the AI age, driving more leads, conversions, and ultimately, success for your local service business.
Key Takeaways:
Embrace AI for Local SEO: Learn to harness the power of AI technologies to optimize your website and content for local search. Understand the pivotal role AI plays in analyzing search trends and consumer behavior, enabling you to tailor your SEO strategies to meet the specific demands of your target local audience. Leverage the Content Factory Model: Discover the step-by-step process of creating SEO-optimized content at scale. This approach ensures a steady stream of high-quality content that engages local customers and boosts your search rankings. Get an action guide on implementing this model, complete with templates and scheduling strategies to maintain a consistent online presence. Maximize ROI with Dollar-a-Day Advertising: Dive into the cost-effective Dollar-a-Day advertising strategy that amplifies your visibility in local searches without breaking the bank. Learn how to strategically allocate your budget across platforms to target potential local customers effectively. The session includes an action guide on setting up, monitoring, and optimizing your ad campaigns to ensure maximum impact with minimal investment.
Yes, It's Your Fault Book Launch WebinarDemandbase
From Blame to Gain: Achieving Sales and Marketing Alignment to Drive B2B Growth.
Tired of the perpetual tug-of-war between your sales and marketing teams? Come hear Demandbase Chief Marketing Officer, Kelly Hopping and Chief Sales Officer, John Eitel discuss key insights from their new book, “Yes, It’s Your Fault! From Blame to Gain: Achieving Sales and Marketing Alignment to Drive B2B Growth.”
They’ll share their no-nonsense approach to bridging the sales and marketing divide to drive true collaboration — once and for all.
In this webinar, you’ll discover:
The underlying dynamics fueling sales and marketing misalignment
How to implement practical solutions without disrupting day-to-day operations
How to cultivate a culture of collaboration and unity for long-term success
How to align on metrics that matter
Why it’s essential to break down technology and data silos
How ABM can be a powerful unifier
In today's digital world, customers are just a click away. "Grow Your Business Online: Introduction to Digital Marketing" dives into the exciting world of digital marketing, equipping you with the tools and strategies to reach new audiences, expand your reach, and ultimately grow your business.
website = https://digitaldiscovery.institute/
address = C 210 A Industrial Area, Phase 8B, Sahibzada Ajit Singh Nagar, Punjab 140308
As 2023 proved, the next few years may be shaped by market volatility and artificial intelligence services such as OpenAI's ChatGPT and Perplexity.ai. Your brand will increasingly compete for attention with Google, Apple, OpenAI, and Amazon, and customers will expect a hyper-relevant and individualized experience from every business at any moment. New state-legislated data privacy laws and several FTC rules may challenge marketers to deliver contextually relevant customer experiences, much less reach unknown prospective buyers. Are you ready?Let's discuss the critical need for data governance and applied AI for your business rather than relying on public AI models. As AI permeates society and all industries, learn how to be future-ready, compliant, and confidentlyscaling growth.
Key Takeaways:
Primary Learning Objective
1: Grasp when artificial general intelligence (""AGI"") will arrive, and how your brand can navigate the consequences. Primary Learning Objective
2: Gain an accurate analysis of the continuously developing customer journey and business intelligence. Primary Learning Objective
3: Grow revenue at lower costs with more efficient marketing and business operations.
Breaking Silos To Break Bank: Shattering The Divide Between Search And SocialNavah Hopkins
At Mozcon 2024 I shared this deck on bridging the divide between search and social. We began by acknowledging that search-first marketers are used to different rules of engagement than social marketers. We also looked at how both channels treat creative, audiences, bidding/budgeting, and AI. We finished by going through how they can win together including UTM audits, harvesting comments from both to inform creative, and allowing for non-login forums to be part of your marketing strategy.
I themed this deck using Baldur's Gate 3 characters: Gale as Search and Astarion as Social
Can you kickstart content marketing when you have a small team or even a team of one? Why yes, you can! Dennis Shiao, founder of marketing agency Attention Retention will detail how to draw insights from subject matter experts (SMEs) and turn them into articles, bylines, blog posts, social media posts and more. He’ll also share tips on content licensing and how to establish a webinar program. Attend this session to learn how to make an impact with content marketing even when you have a small team and limited resources.
Key Takeaways:
- You don't need a large team to start a content marketing program
- A webinar program yields a "one-to-many" approach to content creation
- Use partnerships and licensing to create new content assets
The advent of AI offers marketers unprecedented opportunities to craft personalized and engaging customer experiences, evolving customer engagements from one-sided conversations to interactive dialogues. By leveraging AI, companies can now engage in meaningful dialogues with customers, gaining deep insights into their preferences and delivering customized solutions.
Susan will present case studies illustrating AI's application in enhancing customer interactions across diverse sectors. She'll cover a range of AI tools, including chatbots, voice assistants, predictive analytics, and conversational marketing, demonstrating how these technologies can be woven into marketing strategies to foster personalized customer connections.
Participants will learn about the advantages and hurdles of integrating AI in marketing initiatives, along with actionable advice on starting this transformation. They will understand how AI can automate mundane tasks, refine customer data analysis, and offer personalized experiences on a large scale.
Attendees will come away with an understanding of AI's potential to redefine marketing, equipped with the knowledge and tactics to leverage AI in staying competitive. The talk aims to motivate professionals to adopt AI in enhancing their CX, driving greater customer engagement, loyalty, and business success.
The digital marketing industry is changing faster than ever and those who don’t adapt with the times are losing market share. Where should marketers be focusing their efforts? What strategies are the experts seeing get the best results? Get up-to-speed with the latest industry insights, trends and predictions for the future in this panel discussion with some leading digital marketing experts.
The Strategic Impact of Storytelling in the Age of AI
In the grand tapestry of marketing, where algorithms analyze data and artificial intelligence predicts trends, one essential thread remains constant — the timeless art of storytelling. As we stand on the precipice of a new era driven by AI, join me in unraveling the narrative alchemy that transforms brands from mere entities into captivating tales that resonate across the digital landscape. In this exploration, we will discover how, in the face of advancing technology, the human touch of a well-crafted story becomes not just a marketing tool but the very essence that breathes life into brands and forges lasting connections with our audience.
In the face of the news of Google beginning to remove cookies from Chrome (30m users at the time of writing), there’s no longer time for marketers to throw their hands up and say “I didn’t know” or “They won’t go through with it”. Reality check - it has already begun - the time to take action is now. The good news is that there are solutions available and ready for adoption… but for many the race to catch up to the modern internet risks being a messy, confusing scramble to get back to "normal"
In this humorous and data-heavy session, join us in a joyous celebration of life honoring the long list of SEO tactics and concepts we lost this year. Remember fondly the beautiful time you shared with defunct ideas like link building, keyword cannibalization, search volume as a value indicator, and even our most cherished of friends: the funnel. Make peace with their loss as you embrace a new paradigm for organic content: Pillar-Based Marketing. Along the way, discover that the results that old SEO and all its trappings brought you weren’t really very good at all, actually.
In this respectful and life-affirming service—erm, session—join Ryan Brock (Chief Solution Officer at DemandJump and author of Pillar-Based Marketing: A Data-Driven Methodology for SEO and Content that Actually Works) and leave with:
• Clear and compelling evidence that most legacy SEO metrics and tactics have slim to no impact on SEO outcomes
• A major mindset shift that eliminates most of the metrics and tactics associated with SEO in favor of a single metric that defines and drives organic ranking success
• Practical, step-by-step methodology for choosing SEO pillar topics and publishing content quickly that ranks fast
This session will aim to comprehensively review the current state of artificial intelligence techniques for emotional recognition and their potential applications in optimizing digital advertising strategies. Key studies developing AI models for multimodal emotion recognition from videos, images, and neurophysiological signals were analyzed to build content for this session. The session delves deeper into the current challenges, opportunities to help realize the full benefits of emotion AI for personalized digital marketing.
Conferences like DigiMarCon provide ample opportunities to improve our own marketing programs by learning from others. But just because everyone is jumping on board with the latest idea/tool/metric doesn’t mean it works – or does it? This session will examine the value of today’s hottest digital marketing topics – including AI, paid ads, and social metrics – and the truth about what these shiny objects might be distracting you from.
Key Takeaways:
- How NOT to shoot your digital program in the foot by using flashy but ineffective resources
- The best ways to think about AI in connection with digital marketing
- How to cut through self-serving marketing advice and engage in channels that truly grow your business
Google Ads Vs Social Media Ads-A comparative analysisakashrawdot
Explore the differences, advantages, and strategies of using Google Ads vs Social Media Ads for online advertising. This presentation will provide insights into how each platform operates, their unique features, and how they can be leveraged to achieve marketing goals.
Capstone Project: Luxury Handloom Saree Brand
As part of my college project, I applied my learning in brand strategy to create a comprehensive project for a luxury handloom saree brand. Key aspects of this project included:
- *Competitor Analysis:* Conducted in-depth competitor analysis to identify market position and differentiation opportunities.
- *Target Audience:* Defined and segmented the target audience to tailor brand messages effectively.
- *Brand Strategy:* Developed a detailed brand strategy to enhance market presence and appeal.
- *Brand Perception:* Analyzed and shaped the brand perception to align with luxury and heritage values.
- *Brand Ladder:* Created a brand ladder to outline the brand's core values, benefits, and attributes.
- *Brand Architecture:* Established a cohesive brand architecture to ensure consistency across all brand touchpoints.
This project helped me gain practical experience in brand strategy, from research and analysis to strategic planning and implementation.
From Hope to Despair The Top 10 Reasons Businesses Ditch SEO Tactics.pptxBoston SEO Services
From Hope to Despair: The Top 10 Reasons Businesses Ditch SEO Tactics
Are you tired of seeing your business's online visibility plummet from hope to despair? When it comes to SEO tactics, many businesses find themselves grappling with challenges that lead them to abandon their strategies altogether. In a digital landscape that's constantly evolving, staying on top of SEO best practices is crucial to maintaining a competitive edge.
In this blog, we delve deep into the top 10 reasons why businesses ditch SEO tactics, uncovering the pain points that may resonate with you:
1. Algorithm Changes: The ever-changing algorithms can leave businesses feeling like they're chasing a moving target. Search engines like Google frequently update their algorithms to improve user experience and provide more relevant search results. However, these updates can significantly impact your website's visibility and ranking if you're not prepared.
2. Lack of Results: Investing time and resources without seeing tangible results can be disheartening. The absence of immediate results often leads businesses to lose faith in their SEO strategies. It's important to remember that SEO is a long-term game that requires patience and consistent effort.
3. Technical Challenges: From site speed issues to complex metadata implementation, technical hurdles can be daunting. Overcoming these challenges is crucial for SEO success, as technical issues can hinder your website's performance and user experience.
4. Keyword Competition: Fierce competition for top keywords can make it hard to rank effectively. Businesses often struggle to find the right balance between targeting high-traffic keywords and finding less competitive, niche keywords that can still drive significant traffic.
5. Lack of Understanding of SEO Basics: Many businesses dive into the complex world of SEO without fully grasping the fundamental principles. This lack of understanding can lead to several issues:
Keyword Awareness: Failing to recognize the importance of keyword research and targeting the right keywords in content.
On-Page Optimization: Ignorance regarding crucial on-page elements such as meta tags, headers, and content structure.
Technical SEO Best Practices: Overlooking essential aspects like site speed, mobile responsiveness, and crawlability.
Backlinks: Not understanding the value of high-quality backlinks from reputable sources.
Analytics: Failing to track and analyze data prevents businesses from optimizing their SEO efforts effectively.
6. Unrealistic Expectations and Timeframe: Entrepreneurs often fall prey to the allure of quick fixes and overnight success. Unrealistic expectations can overshadow the reality of the time and effort needed to see tangible results in the highly competitive digital landscape. SEO is a long-term strategy, and setting realistic goals is crucial for success.
#SEO #DigitalMarketing #BusinessGrowth #OnlineVisibility #SEOChallenges #BostonSEO
Unlock the secrets to enhancing your digital presence with our masterclass on mastering online visibility. Learn actionable strategies to boost your brand, optimize your social media, and leverage SEO. Transform your online footprint into a powerful tool for growth and engagement.
Key Takeaways:
1. Effective techniques to increase your brand's visibility across various online platforms.
2. Strategies for optimizing social media profiles and content to maximize reach and engagement.
3. Insights into leveraging SEO best practices to improve search engine rankings and drive organic traffic.
The Forgotten Secret Weapon of Digital Marketing: Email
Digital marketing is a rapidly changing, ever evolving industry--Influencers, Threads, X, AI, etc. But one of the most effective digital marketing tools is also one of the oldest: Email. Find out from two Houston-based digital experts how to maximize your results from email.
Key Takeaways:
Email has the best ROI of any digital tactic
It can be used at any stage of the customer journey
It is increasingly important as the cookie-less future gets closer and closer
1. AN ANALYSIS OF CONSUMER’S
CONSIDERATION TOWARDS THE
PURCHASE OF ELECTRIACAL APPLIANCES
WITH ENERGY LABEL
SPD3125 Marketing Research Class: A02B Group: 7
Tsang Hei Tung, Anna (13626998S)
Wong Wai Kin, Chris (13610687S)
Yeung Wing Shan, Koey (13017542S)
Yim Chin Wai, Molly (13625824S)
Yip Hei Man, Michael (13609850S)
2. Agenda
1. Introduction
2.1 Research Objective
2. 2 Management Decision Problem & Marketing Research
Problem
2. 3 Research Question
2. 4 Hypothesis
2. Research Design
3. 1 Data Collected Method
3. 2 Questionnaire Design
3. Data Findings and Analysis
4. Conclusions
5. 1 Managerial Implication & Recommendations
5. References
6. Appendices
3. Introduction
A survey of 2,014 U.S aged 18 and older was conducted April,2010
→ 67% : consider themselves buyers of green products have retained their level of
green purchases.
→ 25% : increased their green buying in light
A report of Centre for Retail Research (2010)
→ had soared to 56 billion euros ($68.6 billion) in 2009 from 10.3 billion in 2010
→2015, they would approximately double to 114 billion euros
4. Introduction
In Hong Kong, the Electrical and Mechanical
Services Department runs a voluntary
Energy Efficiency Labeling Scheme (EELS)
for appliances and equipment, and for
petrol-powered vehicles.
→ select more energy-efficient products
→ achieve actual energy savings.
5. Research Objective
To analysis the relationship between green perceived value, green
perceived risk, green trust and green purchase intention
Management Decision Problem
• How to enhance the penetration of using the electrical appliances with energy label?
Specific Research Objectives
• How these factors affect the purchase intention differently or jointly?
Marketing Research Problem
1. How do customers decide on purchasing green product?
2. What benefit is expected when customers are purchasing green product?
3. How green products fulfill the expectation of customers?
6. Research Question
1. Green Perceived Value
(How perceived value affect trust and purchase intention?)
2. Green Perceived Risk
(How perceived risk affect trust and purchase intention?)
3. Green Trust
(Is trust important for increasing purchase intention?)
4. Green Purchase Intention
(How purchase intention being affected?)
7. Hypothesis
• H1: Green perceived value is positively associated with green trust.
• H2: Green perceived risk is negatively associated with green trust.
• H3: Green trust is positively associated with green purchase intentions.
• H4: Green perceived value is positively associated with green purchase
intentions.
• H5: Green perceived risk is negatively associated with green purchase
intentions.
• H6: Sex and the purchase of the appliances with Energy Efficiency
Labelling are related
8. Research Design
• Conclusive research design
• Cross-sectional design
• Advantages:
– Easier for testing
– Representative sampling
• Primary Data
– Survey
• Secondary Data
– Journals from Internet
9. Sampling Design
• Nonprobability sampling
– Convenience sampling
– Snowball sampling
• 250 participants
• Choose the sample to send randomly and ask to forward
Data Collection:
• Total returned:250
• Excluding 27 with
no relevant experience
• Final sample size: 223
17. Data Analysis & Findings
Descriptive Statistic
Perceived Value
• Interviewee have the strongest agreement in the electrical appliances with energy
label have an acceptable standard of quality and energy label are economical
Descriptive Statistic
N Minimum Maximum Mean Std. Deviation
Value consistent quality 223 1 7 4.68 1.224
Value reasonably price 222 2 7 4.75 1.063
Value for money 221 2 7 4.69 1.102
value acceptable
quality
223 1 7 5.20 1.052
Value economical 216 1 7 5.07 1.061
Valid N (listwise) 216
18. Data Analysis & Findings
Descriptive Statistic
Perceived Risk
• Fewer people agree that they will suffer less on penalty and loss and harm on the
environment
N Minimum Maximum Mean Std. Deviation
Risk wrong
performance
223 1 7 4.21 1.254
Risk wrong design 222 1 7 4.12 1.293
Risk penalty & loss 220 1 6 3.53 1.343
Risk negatively
affect environment
219 1 7 3.61 1.447
Valid N (listwise) 216
Descriptive Statistic
19. Data Analysis & Findings
Descriptive Statistic
Green Trust
• People do not have a preference towards one of the factor of trust
• An average result towards reliable, dependable, trustworthy, meet customer’s
expectation and keep promises & commitment
Descriptive Statistic
N Minimum Maximum Mean Std. Deviation
Trust reliable 223 2 7 4.89 1.027
Trust dependable 222 2 7 4.97 1.024
Trust trustworthy 223 1 7 5.03 0.986
Trust meet expectations 220 1 7 4.91 1.069
Trust keep promises &
commitments
220 2 7 5.04 1.057
Valid N (listwise) 216
20. Data Analysis & Findings
Descriptive Statistic
Green Purchase Intention
• People are willing to purchase appliances with energy label and continue purchasing
them
• They have a relatively lower intention in spending more on appliances with energy labels.
N Minimum Maximum Mean Std. Deviation
Intension desire to
buy
223 1 7 5.15 1.224
Intension spend more 221 1 7 4.95 1.125
Intension continue to
buy
220 1 7 5.13 1.128
Intension
recommend to others
219 2 7 5.50 0.999
Valid N (listwise) 215
Descriptive Statistic
21. Data Analysis & Findings
H1: Green perceived value is positively associated with green trust.
Correlation
Green
Purchase
Intention
Green
Trust
Green
Perceived
Risk
Green
Perceived
Value
Green Purchase Intention Pearson Correlation
Sig, (1-tailed)
N
1
215
.722**
.000
209
-.163**
.009
212
.531**
.000
209
Green Trust Pearson Correlation
Sig, (1-tailed)
N
.722**
.000
209
1
216
-.147*
.016
210
.576**
.000
207
Green Perceived Risk Pearson Correlation
Sig, (1-tailed)
N
-.163**
.009
212
-.147*
.016
210
1
216
-.144*
.019
210
Green Perceived Value Pearson Correlation
Sig, (1-tailed)
N
.531**
.000
209
.576**
.000
207
-.144*
.019
210
1
213
Correlation
**. Correlation is significant at the 0.01 level (1-tailed).
*. Correlation is significant at the 0.05 level (1-tailed).
r = 0.576
Fair relationship
Positive relationship
p-value=0.01 < 0.01
Accepted the hypothesis
22. Data Analysis & Findings
H2. Green perceived risk is negatively associated with green trust.
Correlation
Green
Purchase
Intention
Green
Trust
Green
Perceived
Risk
Green
Perceived
Value
Green Purchase Intention Pearson Correlation
Sig, (1-tailed)
N
1
215
.722**
.000
209
-.163**
.009
212
.531**
.000
209
Green Trust Pearson Correlation
Sig, (1-tailed)
N
.722**
.000
209
1
216
-.147*
.016
210
.576**
.000
207
Green Perceived Risk Pearson Correlation
Sig, (1-tailed)
N
-.163**
.009
212
-.147*
.016
210
1
216
-.144*
.019
210
Green Perceived Value Pearson Correlation
Sig, (1-tailed)
N
.531**
.000
209
.576**
.000
207
-.144*
.019
210
1
213
Correlation
**. Correlation is significant at the 0.01 level (1-tailed).
*. Correlation is significant at the 0.05 level (1-tailed).
r = -0.147
Weak relationship
Negative relationship
p-value=0.016 < 0.05
Accepted the hypothesis
23. Data Analysis & Findings
H3. Green trust is positively associated with green purchase intentions.
Correlation
Green
Purchase
Intention
Green
Trust
Green
Perceived
Risk
Green
Perceived
Value
Green Purchase Intention Pearson Correlation
Sig, (1-tailed)
N
1
215
.722**
.000
209
-.163**
.009
212
.531**
.000
209
Green Trust Pearson Correlation
Sig, (1-tailed)
N
.722**
.000
209
1
216
-.147*
.016
210
.576**
.000
207
Green Perceived Risk Pearson Correlation
Sig, (1-tailed)
N
-.163**
.009
212
-.147*
.016
210
1
216
-.144*
.019
210
Green Perceived Value Pearson Correlation
Sig, (1-tailed)
N
.531**
.000
209
.576**
.000
207
-.144*
.019
210
1
213
Correlation
**. Correlation is significant at the 0.01 level (1-tailed).
*. Correlation is significant at the 0.05 level (1-tailed).
r = 0.722
Strong relationship
Positive relationship
p-value=0.000 < 0.01
Accepted the hypothesis
24. Data Analysis & Findings
H4. Green perceived value is positively associated with green purchase
intentions.
Correlation
Green
Purchase
Intention
Green
Trust
Green
Perceived
Risk
Green
Perceived
Value
Green Purchase Intention Pearson Correlation
Sig, (1-tailed)
N
1
215
.722**
.000
209
-.163**
.009
212
.531**
.000
209
Green Trust Pearson Correlation
Sig, (1-tailed)
N
.722**
.000
209
1
216
-.147*
.016
210
.576**
.000
207
Green Perceived Risk Pearson Correlation
Sig, (1-tailed)
N
-.163**
.009
212
-.147*
.016
210
1
216
-.144*
.019
210
Green Perceived Value Pearson Correlation
Sig, (1-tailed)
N
.531**
.000
209
.576**
.000
207
-.144*
.019
210
1
213
Correlation
**. Correlation is significant at the 0.01 level (1-tailed).
*. Correlation is significant at the 0.05 level (1-tailed).
r = 0.531
Fair relationship
Positive relationship
p-value=0.01 < 0.01
Accepted the hypothesis
25. Data Analysis & Findings
H5. Green perceived risk is negatively associated with green purchase
intentions.
Correlation
Green
Purchase
Intention
Green
Trust
Green
Perceived
Risk
Green
Perceived
Value
Green Purchase Intention Pearson Correlation
Sig, (1-tailed)
N
1
215
.722**
.000
209
-.163**
.009
212
.531**
.000
209
Green Trust Pearson Correlation
Sig, (1-tailed)
N
.722**
.000
209
1
216
-.147*
.016
210
.576**
.000
207
Green Perceived Risk Pearson Correlation
Sig, (1-tailed)
N
-.163**
.009
212
-.147*
.016
210
1
216
-.144*
.019
210
Green Perceived Value Pearson Correlation
Sig, (1-tailed)
N
.531**
.000
209
.576**
.000
207
-.144*
.019
210
1
213
Correlation
**. Correlation is significant at the 0.01 level (1-tailed).
*. Correlation is significant at the 0.05 level (1-tailed).
r = -0.163
Weak relationship
Negative relationship
p-value=0.009< 0.01
Accepted the hypothesis
26. Data Analysis & Findings
Regression
• The table showed the relation between green perceived value, green perceived risk and
green trust
• R= 0.581 and R Square=0.337
• Green perceived value and green perceived risk can only predict 33.7% green trust
• → This is not a good predictor
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
1 .581a .337 .331 .61673
Model Summary
a. Predictors: (Constant), New Green_Perceived_value, New Green_Perceived_risk
27. Data Analysis & Findings
Regression
• The model-F can accurately explain variation in green trust
• → The significant value= 0.000 = Low probability variation
• Green perceived value and green perceived risk explains a significant portion of the
variation in green trust
• → P=0.000 < 0.001
• Change in green perceived value and green perceived risk resulted in changes in green
trust
Model
Sum of
Squares
df Mean Square F Sig.
1 Regression
Residual
Total
38.921
76.450
115.372
2
201
203
19.461
.380
51.165 .000a
ANOVAb
a. Predictors: (Constant), New Green_Perceived_value, New Green_Perceived_risk
b. Dependent Variable: New Green_Trust
28. Data Analysis & Findings
Regression
1) Green perceived risk can lead to a decrease in green trust
→ Negative regression coefficient (B=-0.052), p>0.05, reject the hypothesis.
2) Green perceived value can lead to an increase in green trust
→ Positive regression coefficient (B=0.587, p<0.01).
→ The green trust is increased by 58.7%. Accept the hypothesis
Model B Sig.
1 (Constant)
New_Green_Perceived _risk
New_Green_Perceived _Value
2.296
-.052
.587
.000
.231
.000
Coefficients a
a. Dependent Variable: New_Green_Trust
29. Data Analysis & Findings
Regression
• The correlation coefficient is high at 0.758
• R= 0.758 and R Square=0.575
• Green perceived value , green perceived risk and green trust can predict 57.5% green
purchase intention
• → This is a fair predictor for green purchase intention
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
1 .758a .575 .569 .60128
Model Summary
a. Predictors: (Constant), New Green_Trust, New Green_Perceived_risk,
New Green_Perceived_value
30. Data Analysis & Findings
Regression
• The model-F can accurately explain variation in green trust
→ The significant value= 0.000 = Low probability variation
• Green perceived value and green perceived risk explains a significant portion of the
variation in green trust
→ P=0.000 < 0.001
• Change in green perceived value and green perceived risk resulted in changes in green
trust
ANOVAb
a. Predictors: (Constant), New Green_Trust, New Green_Perceived_value, New Green_Perceived_risk
b. Dependent Variable: New Green_Purchase_intentino
Model
Sum of
Squares
df Mean Square F Sig.
1 Regression
Residual
Total
95.903
70.860
166.764
3
196
199
31.968
.362
88.423 .000a
31. Data Analysis & Findings
Regression
• B= -0.057 → Negative
• p>0.05 → Reject
Green perceived risk ↓ Green purchase
intention
• B=0.253 → Positive
• p<0.01 → Accept
Green perceived value ↑ Green
purchase intention
• B=0.738 → Positive
• p<0.01 → Accept
Green trust ↑ Green purchase intention
Model B Sig.
1 (Constant)
New Green_Perceived _risk
New Green_Perceived _Value
New Green_Trust
.407
-.057
.253
.738
.295
.183
.001
.000
Coefficients a
a. Dependent Variable: New_Green_Purchase_Intention
32. Data Analysis & Findings
Crosstab
H0: Sex and electrical appliances with "energy label" purchase are not related
H6: Sex and electrical appliances with "energy label" purchase are related
→ Chi-square statistics is 2.55 , Computed p-value is 0.110 >0.05
→ Accept:H0 and Reject: H6
→ Purchasing electrical appliances with "energy label" is not depends on gender
Chi- Square Tests
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 12. 10.
b. Computed only for a 2x2 table
Value df
Asymp. Sig. (2-
sided)
Exact Sig. (2-
sided)
Exact Sig.
(1- sided)
Pearson Chi-Square
Continuity Correction b
Likelihood Ratio
Fisher’s Exact Test
Linear-by-Linear Association
N of Valid Cases
2.559a
1.946
2.546
2.549
250
1
1
1
1
.110
.163
.111
.110
.151 .082
33. Conclusion
Consumers
have an average perception on green trust
feel comfort overall to continue buying the product
Construct Relationship
Green perceived value and green perceived risk have only affect 33.7% of green trust
Positive relations between green perceived value and trust, green trust and purchase intention,
green perceived value and purchase intention
No direct relationship between perceived risk and purchase intention
No relationship between gender and purchase intention
34. Recommendations
Perceived Value
Q3: The electrical appliances with energy label have consistent quality
Q5: The electrical appliances with energy label offer value for money
Green Purchase Intention
Q18: I am willing to spend a little more money to buy the electrical appliances with energy label
The lowest mean score
We recommend :
• Telling the people about the amount of money they can save
• Emphasizing the benefit people can enjoy beside saving money
• Promoting environmental protection through advertising and other social media channels
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Nowadays, many companies are seeking sustainability and green marketing to create a competitive advantage in the global marketplace.
According to a survey of 2,014 U.S. adults was conducted April, 2010 by SCA and Harris Interactive, overall, two-thirds (67%) of U.S. adults who consider themselves buyers of green products have retained their level of green purchases. Additionally, 25% have increased their green buying in light of the recent changes in the economy.
Like many Asian cities, Hong Kong suffers high levels of air pollution, high levels of exposure to severe traffic noise, high levels of garbage disposal etc.
Therefore the Hong Kong Electrical and Mechanical Services Department (EMSD) runs an Energy Efficiency Labeling Scheme (EELS) for appliances and equipment for example, refrigerators, washing machines and dehumidifiers.
The EELS aims to help consumers select more energy-efficient products, increase public awareness of the importance of using energy-efficient products, achieve actual energy savings etc.
The aim of this research is to analysis the relationship between green perceived value, green perceived risk, green trust and green purchase intention. These constructs are the important factors that affect their purchase decision of electrical appliances with energy label.
The management decision problem are “How to enhance the penetration of using the electrical appliances with energy label?”
We set the question “How these factors affect the purchase intention differently or jointly?” as our Specific Research objective
And the question “How do customers decide on purchasing green product?”, “What benefit is expected when customers are purchasing green product?”and “How green products fulfill the expectation of customers?”as our Marketing Research Problem.
Further on, we set 4 research question based on our objective, we set “How perceived value affect trust and purchase intention?”, “How perceived risk affect trust and purchase intention?”,” Is trust important for increasing purchase intention?”and “How purchase intention being affected?”as our research question for Green Perceived Value, Green Perceived Risk, Green Trust and Green Purchase Intention .
Since the four constructs are related, we’ve set 6 Hypothesis for it.
For first hypothesis, past research posits that there is a positive relationship between perceived value and customer trust, since high level of perceived value can increase post-purchase confidence of the product
The second hypothesis, buyers are unwilling to purchase a product because of their distrust of the seller due to the information asymmetry. If consumers perceive high risk towards a product, they would be reluctant to trust the product There is a relationship between risk perceptions and effect on trust.
The third, buyers would have had a trust experience with the seller, they would possess a higher level of purchase intentions. Thus, consumer trust is an antecedent of customer purchase intentions
The fourth, perceived value is related to the perception of a product’s value, so it can build up a positive word-of-mouth effect and raise purchase intentions. Poor perceived value can result in loss of consumer purchase intentions. If consumers perceive that the value of a product is higher, they are more likely to purchase the product.
The fifth, Perceived risk has negative influence on the purchase decision of customers. The reduction of perceived risk leads to the increase of purchase probability and to the rise of customer purchase intentions, so perceived risk is negatively associated with purchase intention.
And the sixth hypothesis, the purchase behavior of electrical appliances with "energy label" may be different depend on their sex.
Conclusive research design and Cross-sectional design are used for our research design since they are easy for testing and they are representative sampling The research is collected from both primary and secondary data. We conducted the questionnaire survey as the primary data, and Journals from Internet as our secondary data.
On sampling design, we adopt a nonprobability sampling include convenience sampling and snowball sampling, which we asks participants to share with others. There are total 250 participants which we choose the sample to send and forward again to gain enough respondents.
The questionnaire items were designed in English. Totally 250 questionnaires were received through Facebook and face-to-face randomly response in convenience and snowball sampling of non-probability sampling technique. The sample size would be 223 exclude 27 with no relevant experience.
There is a screening question of asking the experience of green product purchased. The nominal, ordinal and interval scaling are used in this questionnaire for asking respondents in different questions about the four constructs. To study the objective of this study, the frequency, descriptive statistics, ANOVA test, Chi-Square analysis, correlation analysis and regression have been applied. At last follow by the personal information to design our questionnaire.
These are the construct of our questionnaire, which you can see that from Q3 to Q7, which include…
Question about Green Perceived Risk are asked on 8-11, which include…
Question about Green trust are asked on 12-16, they include…
Question about Green purchase intention are asked on 17-20, they include…
From the result collected from our questionnaire, 55.2% of the interviewees are female and 44.8% are male.
The largest age group are 18-23, they hold 54.8% of the hold group, follow by age range from 24-29(19.6%)
The highest group of education level will be University or above, which cover 52% of the whole group, follow by 25.2% of the group Associate degree/Higher degree.
The highest income level will be more than $25,000 dollars , which cover 52.8% of the whole group.
In the area of green perceived value, since the highest mean score are 5.2 and 5.07, this indicate that interviewees have the strongest agreement with the statement “electrical appliances with energy label have an acceptable standard of quality” and “electrical appliances with energy label are economical”.
For the Perceived risk, the lowest mean score are the question asking about risk on penalty and loss and risk on negatively affect environment. This shows that fewer people believe that they will suffer penalty and loss and harm on the environment by using the electrical appliance with energy label.
On green trust, people do not have preference towards one of the statement of trust. It shows an average result towards reliable, dependable, trustworthy, meet customer’s expectation and keep promises & commitment.
For Purchase intention, the highest and the second highest mean are the desire to purchase and consistency in purchasing the appliances with energy label. It shows that people are willing to purchase appliances with energy label and continue purchasing them. However, they have a relatively lower intention in spending more on appliances with energy labels.
H1. Green perceived value is positively associated with green trust.
The value of r is 0.576, is shown that the relationship between the two variables are fair. And the computed p-value is 0.000 which is smaller than p=0.01, indicating that the hypothesized relationship is significant. Thus, the comment of respondents about the green perceived value is positive related to the degree of the confidence of the green product of them.
H2. Green perceived risk is negatively associated with green trust.
The value of r is -0.147, is close to zero that the relationship between the two variables are very weak. And the computed p-value is 0.016 which is smaller than p=0.05, indicating that the hypothesized relationship is significant. Thus, the comment of respondents about the green perceived risk is lowly negative related to the trust of respondents in green products.
H3. Green trust is positively associated with green purchase intentions.
The value of r is 0.722, is near to 1 that the relationship between the two variables are strong. And the computer p-value is 0.000 which is smaller than p=0.01, indicating that the hypothesized relationship is significant. Thus, the comment of respondents about the green trust is highly positive related to the degree of the trust of respondents in green products.
H4. Green perceived value is positively associated with green purchase intentions.
The value of r is 0.531, is around a half that the relationship between the two variables are fair. And the computer p-value is 0.000 which is smaller than p=0.01, indicating that the hypothesized relationship is highly significant. Thus, the comment of respondents about the green perceived value is positively related to the degree of the purchase intention of the green product of them.
H5. Green perceived risk is negatively associated with green purchase intentions.
The value of r is -0.163, is close to zero that the relationship between the two variables are very weak. And the computer p-value is 0.009 which is smaller than p=0.01, indicating that the hypothesized relationship is significant. Thus, the comment of respondents about the green perceived risk is lowly negative related to the degree of the purchase intention of the green product of them.
The model summary table shows the relation between green perceived value, green perceived risk and green trust. “R” is at 0.581. The R Square of 0.337 indicates that green perceived value and green perceived risk can only predict 33.7% green trust. In conclusion, green perceived value and green perceived risk is not a good predictor for green trust.
Form the ANOVA table, the model-F can accurately explain variation in green trust, since the significant value of 0.000 informs us that the probability is very low that the variation explained by the model is due to chance. Green perceived value and green perceived risk explains a significant portion of the variation in green trust since the computed p value is 0.000, which is smaller than p=0.001. In conclusion, change in green perceived value and green perceived risk resulted in changes in green trust.
From the coefficients table, green perceived risk can lead to a decrease in green trust as evidenced by the negative coefficients (B=-0.052). Since p>0.05, This shows that there are no significant relation between risk and trust, hence the hypothesis will be rejected.
Moreover, green perceived value can lead to an increase in green trust as evidenced by the positive coefficients (B=0.587, p<0.01). For an increase in green perceived value, green trust is increased by 58.7%. Thus, we accept the hypothesis.
The model summary table showed that R is high at 0.758. The correlation coefficient between green perceived value, green perceived risk, green trust and green purchase intention is high at 0.758. R square of 0.575 indicates that 57.5% of the variances in the green purchase intention can be explained by green perceived value, green perceived risk and green trust. In conclusion, green perceived value, green perceived risk and green trust is a fair predictor for green purchase intention.
From the ANOVA table, the model-F can accurately explain variation in green trust, since the significant value of 0.000 informs us that the probability is very low that the variation explained by the model is due to chance. Green perceived value, green perceived risk and green trust explains a significant portion of the variation in the green purchase intention since the computed p value is 0.000, which is smaller than p=0.001. In conclusion, changes in green perceived value, green perceived risk and green trust resulted in significant changes in green purchase intention.
Green perceived risk can lead to a decrease in green purchase intention as evidenced by the negative regression coefficient (B=-0.057). Since p>0.05, we rejected the hypothesis.
Moreover, green perceived value can lead to an increase in green purchase intention since the regression coefficient is positive (B=0.253, p<0.01). For an increase in green perceived value, the green purchase intention is increased by 25.3%. Thus, we accept the hypothesis.
Also, green trust can lead to an increase in green purchase intention since the regression coefficient is positive (B=0.738, p<0.01). For an increase in green trust, the green purchase intention is increased by 73.8%. Thus, we accept the hypothesis.
In conclusion, after conducting descriptive analysis, we found that the green perceived value and green perceived risk have only affect 33.7% of green trust. To be more adequate, more variables should be considered to predict green trust.
We also found that consumers have an average perception on green trust, which indicated that consumers have an average inception on trusting the labeled electrical appliance.
In the part of purchase intention, the highest score mean are the desire and consistency on buying the labeled electrical appliance, which is a good sign that consumer feel comfort overall to continue buying the product.
For the factors affecting customer’s purchase behavior of electrical appliances with "energy label", we accepted the positive relations between green perceived value and trust (H1), green trust and purchase intention (H3), green perceived value and purchase intention (H4).
However, the result showed that there is no direct relationship between perceived risk and purchase intention as people would like to buy electrical appliances even they have high risk or with no energy label.
Moreover, we can figure out that there are no relationship between the gender and the purchase intention from the above analysis.
After the analysis, the lowest mean score in perceived value are the statement asking about the consistent quality(Q3) and value for money(Q5). Moreover, in Q18 asking about whether interviewees willing to spend more for the electrical appliances with energy label has the lowest mean score which is 4.95.
We recommend that the government should tell the people about the amount of money they can save by using electrical appliances with energy label compare to those without the label to enhance the perceived value of the electronic appliance with energy label.
Moreover, government should also emphasis the benefit people can enjoy by using these appliances beside saving money, such as environmental protection through advertising and other social media channels.