University of Florida Thesis Or Dissertation

PREDICTING TAIWANESE GENERAL PUBLIC’S SUPPORT OF LOCALLY GROWN FOOD USING AWARENESS OF FOOD INSECURITY ISSUES

PEI-WEN HUANG

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2015

To my family and all the people in Taiwan

ACKNOWLEDGMENTS

The completion of my doctoral program would not be possible without all the love, support, assistance, and guidance I have received from many individuals. First of all, I would like to thank my adviser, Dr. Alexa Lamm, for all the support, encouragement, and guidance she had provided me. I would have never made it this far and feel so engaged in extension without her advice. I am grateful for having various opportunities and experiences in extension, such as an internship, research projects, conference papers, and publications, of which Dr. Lamm encouraged and supported me to work on throughout my time in the Agricultural Education and Communication (AEC) program. She had provided my assistantship, helped me expand my extension experiences, and guided me to reach my career goal. This dissertation study would not be possible without her support of my idea of assisting my home country, Taiwan. I would also like to thank my committee members, Dr. Joy Rumble, Dr. Amy Harder, and

Dr. Treadwell, for their advice and support to strengthen my program and study. I appreciated all the challenges they had provided during my program to make me become a real, qualified doctor of Philosophy.

I would also like to thank Dr. Ed Osborne for editing and providing insightful feedback for my draft dissertation. My appreciation has to be given to Dr. Osborne for all the support and advice from financial assistantship to academic awards and honors, all of which have strengthened my competency and confidence as a student and a professional. I have to thank Dr. James Dyer for encouraging me to apply for the AEC extension education program for me when I was lost and seeking my career. Additional appreciation has to be given to Dr. Aparna Gazula for inspiring me what I would like to do for my career and guiding me during my internship with her in the Alachua County

Extension. I would like to thank Dr. Eric Simonne as well for consulting about my career and supporting me for all the professional events and activities.

Other than faculty members, I have to thank Ms. Debra Anderson who had helped me overcome the frustration and been extremely caring about my success. I appreciated her understanding about the difficulties international students have and willingness to support my living in the U.S. I would like to thank my loving roommates,

Yu-Chien Tseng and Ron-Chi Kuo, who have made my Ph.D student life more fun, less intense, and made Gainesville feel more like home with two sweet siblings. I would also like to thank my colleagues in the AEC department, who were always inspiring, shared the sweetness and bitterness of the graduate student life with me, and supported me to get closer and closer to being a real professional. Special thanks has to be given to

Shuyang Qu who had been supportive in career and life throughout my time in the AEC program, especially for sharing the good and bad about being one of the few international students in the program. Another special thanks has to be given to Dr.

Milton Newberry who had been my mentor providing me valuable advice and support about how to better acclimate to American life since my very first day in AEC.

Appreciation must also be given to Dr. Yi-Ting Chung and Dr. Yu-Sheng Hsieh who had helped review the instrument of this study and provide helpful suggestions and feedback about how to properly conduct a social science survey to fit the environment in

Taiwan and strengthen the study. This study could not have been sufficiently accomplished without Dr. Chung and Dr. Hsieh’s assistance. I have to particularly thank

Dr. Hua-Jen Kuo for actively helping me to connect to other Taiwanese scholars

working in agricultural issues. Dr. Kuo served as a critical connector for this study and I would have lost a lot of time without his assistance.

This study would not be successful without the assistance from my dear friend,

Yi-Lin Chen, who has been working as an English-Traditional Chinese translator and provided valuable and valid suggestions for the instrument translation revision. I thank all the Taiwanese students and Taiwanese residents living in Gainesville, who helped to respond the pilot-test survey. This study would not be accomplished successfully without such a group of good-hearted and supportive Taiwanese people.

Most importantly, I would like to thank my family. I am appreciative that I have been fully supported to do what I love to do for my life with full of love by my family, even though there had been so many others challenging my decision. I give extreme thanks to my Mom, Chi-sheng Kuo, who had been extraordinarily devoted to support me, regardless where I am and what I am working on. My Mom always told me how much she enjoyed talking with me since she can always learn something new and see my growth over time. This is the best and warmest encouragement that supported me throughout my time in the doctoral program. I hope I have made my Dad proud of my accomplishment and I know he has always been watching me from Heaven.

In the very end, I would like to thank my fiancé, Dean Kuan-wen Chen, for his full love and support. I appreciate that he always has his faith in me and has been with me regardless good or bad. I know I have become a better person based on his encouragement and love.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 11

LIST OF FIGURES ...... 12

ABSTRACT ...... 13

CHAPTER

1 INTRODUCTION ...... 15

Global Food Security Issues ...... 15 Caribbean Countries ...... 16 Eastern Asian Countries ...... 17 Global Trading Policies ...... 20 Benefits ...... 21 Impacts ...... 21 Agriculture in Taiwan ...... 22 History Background ...... 22 Current Industry ...... 24 Current Problems ...... 26 Food Insecurity in Taiwan ...... 27 Causes of Food Insecurity ...... 28 Conflict with Government Policy ...... 30 Impacts to the Local Agricultural Industry ...... 31 Impacts to Local Consumers ...... 32 Agricultural Extension in Taiwan ...... 34 History ...... 34 System ...... 35 Services ...... 36 Statement of the Problem ...... 37 Purpose and Objectives ...... 37 Significance of the Study ...... 38 Definition of Terms ...... 39 Assumption ...... 40 Summary ...... 41

2 LITERATURE REVIEW ...... 43

Food Consumption Behaviors in Taiwan ...... 43 Awareness of Food Insecurity in Taiwan ...... 46 Attitudes toward Local Agriculture in Taiwan ...... 48 Perceptions of Local Food in Taiwan ...... 51

Theory of Planned Behavior ...... 55 Behavioral Beliefs ...... 56 Normative Beliefs ...... 57 Control Beliefs ...... 58 Intention...... 59 Behavior ...... 60 Social Cognitive Theory ...... 61 Conceptual Model of Support for Locally Grown Food in Taiwan ...... 65 Planned Behavior Phase ...... 65 Social Cognition Phase ...... 70 Summary ...... 72

3 RESEARCH METHODS ...... 75

Overview ...... 75 Research Objectives ...... 75 Research Design ...... 76 Population and Sample ...... 77 Survey Error ...... 78 Instrumentation ...... 80 Independent Variables ...... 87 Dependent Variables ...... 87 Pilot Study ...... 88 Potential Validity Threats ...... 89 Reliability ...... 91 Data Collection ...... 92 Procedure ...... 92 Data Analysis ...... 93 Descriptive Statistics ...... 94 Correlational Statistics ...... 95 Multiple Regression Modeling ...... 97 Limitations ...... 98 Summary ...... 100

4 RESULTS ...... 104

Description of Demographics, Food Insecurity Items, Attitudes toward Locally Grown Food, Subjective Norm, Perceived Behavioral Control, and Intention to Purchase Locally Grown Food ...... 105 Demographics ...... 105 Original respondents ...... 105 Weighted respondents ...... 106 Food Insecurity Items ...... 107 Perceived knowledge level...... 107 Awareness ...... 107 Past experience ...... 108 Attitudes ...... 108

Subjective Norms ...... 109 Perceived Behavioral Control ...... 109 Intention...... 109 Relationships between Constructs Associated with Food Insecurity, Locally Grown Food, and Demographical Variables ...... 110 Food Insecurity Items and Intention ...... 110 Attitude, Subjective Norm, Perceived Behavioral Control, and Intention ...... 111 Demographic Characteristics and Intention ...... 111 Inter-correlations between Research Constructs and Demographic Characteristics ...... 112 Predicting Purchase of Locally Grown Food Using Demographics, Food Insecurity Items, Attitudes, Subjective Norm, and Perceived Behavioral Control ...... 115 Summary ...... 118

5 CONCLUSIONS, IMPLICATIONS, AND RECOMMENDATIONS ...... 132

Conclusions ...... 132 Demographics ...... 132 Food Insecurity Issues ...... 133 Knowledge ...... 133 Awareness ...... 134 Experience ...... 135 Attitudes toward Locally Grown Food and Perceived Importance of Agriculture ...... 135 Subjective Norm of Purchasing Locally Grown Food ...... 136 Perceived Behavioral Control of Purchasing Locally Grown Food ...... 137 Intention to Purchase Locally Grown Food ...... 137 Key Relationships between Variables ...... 138 Prediction of Locally Grown Food Purchases ...... 141 Implications and Recommendations ...... 144 Online Survey Opportunities ...... 149 Extension and Education Opportunities ...... 150 Marketing Opportunities ...... 153 Research Opportunities ...... 154 Summary ...... 156

APPENDIX

A FOOD INSECURITY AND SUPPORT OF LOCALLY GROWN FOOD SURVEY (ENGLISH VERSION)...... 158

B FOOD INSECURITY AND SUPPORT OF LOCALLY GROWN FOOD SURVEY (TRADITIONAL CHINESE VERSION) ...... 174

C IRB APPROVALS FOR PROTOCOL #2015-U-968 ...... 189

LIST OF REFERENCES ...... 193

BIOGRAPHICAL SKETCH ...... 210

LIST OF TABLES

Table page

3-1 Reliability Coefficients of the Index Scores of the Constructs ...... 102

3-2 Weight Coefficients of Sex, Age, and City ...... 103

3-3 Normality of the Index Scores...... 103

4-1 Demographics of the Respondents ...... 120

4-2 Knowledge Level of Food Insecurity Issues in Taiwan ...... 123

4-3 Awareness of Food Insecurity Issues in Taiwan ...... 123

4-4 Experience of Food Insecurity Issues in Taiwan ...... 124

4-5 Attitudes toward Taiwan’s Locally Grown Food ...... 124

4-6 Perceived Importance of Agriculture in Taiwan ...... 124

4-7 Subjective Norms of Purchasing Locally Grown Food ...... 125

4-8 Perceived Behavioral Control of Purchasing Locally Grown Food ...... 125

4-9 Intention to Purchase Locally Grown Food ...... 126

4-10 The Means and Standard Deviations of the Research Constructs ...... 126

4-11 Inter-correlations between the Research Constructs and Demographics of Sex, Age, and Income ...... 127

4-12 Inter-correlations between the Research Constructs and Demographics ...... 128

4-13 Inter-correlations between the Research Constructs and Demographics ...... 129

4-14 Inter-correlations between Specific Demographics ...... 130

4-15 Sequential Multiple Linear Regression Model Predicting Intention to Purchase Locally Grown Food...... 130

4-16 Regression Coefficients of the Sequential Multiple Linear Regression Model Predicting Intention to Purchase Locally Grown Food ...... 131

LIST OF FIGURES

Figure page

2-1 The model of Theory of Planned Behavior...... 73

2-2 The model of Social Cognitive Theory...... 73

2-3 Conceptual model of support for locally grown food in Taiwan...... 74

3-1 Map of the Northern Region of Taiwan ...... 102

5-1 Concluded conceptual model of support for locally grown food in Taiwan...... 157

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

PREDICTING TAIWANESE GENERAL PUBLIC’S SUPPORT OF LOCALLY GROWN FOOD USING AWARENESS OF FOOD INSECURITY ISSUES

Pei-wen Huang

December 2015

Chair: Alexa J. Lamm Major: Agricultural Education and Communication

Taiwan is a country struggling with national food insecurity issues due to limited natural resources, a large population, a small farm operation system, the impact of the openness of global trade for agricultural products, and conflicts between government policy and the agricultural industry. Currently, the food self-sufficiency rate has dropped to 33% weighted by calories in Taiwan with almost 70% of the food coming from imports which could lead to severe national security issues if the imported sources were shut down suddenly. As a result, problem-solving strategies are needed to alleviate the import-reliance situation in Taiwan to ensure national food security.

The purpose of this study was to examine the Taiwanese general public’s knowledge, awareness, and experiences with food insecurity issues; attitudes, subjective norms, perceived behavioral control, and intention associated with locally grown food; and to predict purchasing intention of locally grown food based on these indicated food insecurity and locally grown food related factors. An online survey was used to collect data from the general public living in the Northern Region of Taiwan. The instrument was researcher-developed to measure the respondents’ opinions of food insecurity and locally grown food. Descriptive, correlational, and multiple linear

regression analysis were used to examine how locally grown food purchasing intention of Taiwanese general public can be predicted and influenced by their knowledge, awareness, and experiences with food insecurity issues; and attitudes, subjective norms, and perceived behavioral control related to locally grown food purchases.

The findings of this study indicated the respondents perceived they are not at all or slightly knowledgeable, received fair awareness scores, and had certain experiences with food insecurity issues in Taiwan. Moreover, they reported positive attitudes toward locally grown food, high perceived importance of agriculture, high support from important individuals to purchase locally grown food and great behavioral control over purchasing locally grown food. Knowledge, awareness, subjective norms, perceived behavioral control, and selected demographic characteristics were revealed as significant predictors of locally grown food purchase intention. The implications and recommendations of this study shed light on efforts Taiwan Extension should take regarding food insecurity issues and the local food movement.

CHAPTER 1 INTRODUCTION

Taiwan is an island country with one of the highest population densities in the world; more than 23 million people live in approximately 14,400 square miles (Ministry of the Interior, 2014). Due to the geographical limitations of the entire land area and land available for agricultural cultivation on the island, feeding the increasing population has been a challenge (Peng, 2011). In this introductory chapter, an overview of global food security issues will be provided, followed by a discussion of global trading policies.

Agriculture in Taiwan will then be introduced and food insecurity issues in Taiwan will also be examined. In the latter part of this chapter, the purpose of the study, research objectives, and definitions of terms will be provided, while assumptions of this study will also be discussed. A chapter summary will be presented as a conclusion to this chapter.

Global Food Security Issues

According to the definition provided by the Food and Agriculture Organization

(FAO) from the World Food Summit (1996), food security “exists when all people, at all times, have physical and economic access to sufficient, safe, and nutritious food that meets their dietary needs and food preferences for an active and healthy life” (para. 1).

According to FAO (2013), one-eighth of the world’s population had insufficient protein and energy access in 2011-2013. At the national level, food security can be a critical issue in different countries due to different reasons (Godfray et al., 2010). In developing countries, particularly in sub-Saharan African and South Asian countries, where food security has been studied for years, increased population, poverty, poor agricultural investment, water scarcity, climate change, and diseases have been cited as factors impacting food security (Rosegrant & Cline, 2003). For developed countries, food

security has been a hidden threat and has received little public attention (FAO, 2011).

The majority of people in developed countries have been unaware of the food security issue because of their high socioeconomic status, which has allowed them access to sufficient food (FAO, 2011). However, due to the unstable food import sources caused by increased population and climate change, precautions against a potential food insecurity crisis have been needed on an international scale (Schmidhuber & Tubiello,

2007). Food security issues have been situational. Due to the complex nature of food security, dimensions of availability, access, utilization, stability, and situations specific to different countries should be considered in order to explain the issue thoroughly (FAO,

2013).

Climate limitations, conflict, weak infrastructure, and limited livelihood have negatively impacted national food security in countries where severe food insecurity has been reported, such as sub-Saharan African, the Horn of African, and South Asian countries (FAO, 2000; FAO, 2013). However, the causes of food insecurity in these countries are different from the causes in Taiwan, therefore the discussion in this chapter is focused on Caribbean countries and Eastern Asian countries due to their similarity to Taiwan regarding food security issues, the island country environment, and even cultural background.

Caribbean Countries

Caribbean countries’ economies have primarily relied upon exports, whereas

“most of these [Caribbean] countries are net food importers” (Deep Ford, dell’Aquila, &

Conforti, 2007, p. 1). To combat the limited resources in island countries, trade could be used to expand the available resources. However, the openness of trade in Caribbean countries has led to an increased reliance on food imports that may cause food

insecurity (Deep Ford et al., 2007). Countries in the Caribbean have had different levels of openness to trade, rates of food imports and exports, agricultural industry structure, and percentage of undernourishment in the population, due to their unique industry patterns (Deep Ford et al., 2007). For example, the ratio of imports to exports in 2004 was high in Haiti (22:1) and Antigua and Barbuda (21:1), while Belize (0.4:1), Guyana

(0.4:1), and the Dominican Republic (0.8:1) had low numbers in the ratio of imports to exports (Deep Ford et al., 2007). Overall, global trade liberalization has contributed to an increase in food insecurity, the loss of rural livelihoods, changes in domestic production and consumption patterns, and an increase in health problems in the

Caribbean countries (Deep Ford et al., 2007).

In Cuba, due to the cessation of the premium trading contract with the Soviet

Union, reduced sugar exports have led to decreased oil imports and have further caused the discontinuation of the agricultural mechanization program (Deere, Pérez,

& Gonzales, 1994). As a result, the Cuban government divided the large-scale government-owned farmland into small farms and recruited labors for farm operations

(Woodhouse, 2010). By implementing waste recycling practices and organic pest management practices, Cuba’s favorable climate has provided an environment allowing for year-round production, which has led to sufficient food production for the Cuban population (Woodhouse, 2010).

Eastern Asian Countries

Asia is the most populous continent with a population of 4.3 billion people, or about 60% of the global population. The major challenges Asia has confronted have been associated with securing adequate food supplies resulting from rising food prices due to the increased food demand without a matching supply; and declining agricultural

investments in production, research, and infrastructure (Amerasinghe & Furagganan,

2010). Moreover, climate change is expected to adversely impact at least 50 million people in Asia as a result of destructive storms, floods, and droughts damaging the major production areas (FAO Regional Office for Asia and the Pacific, 2010).

China’s large population has led to limited farming resources shared per capita

(Chen, 2014). Food security issues in China have been associated with its rapid growth in development leading to pollution of natural resources, over-urbanization, and deterioration in water and soil quality (Brown, 1995; Chen, 2014). The growing population has influenced people’s increased demand of food (Chen, 2014). Currently, food production in China can provide a sufficient food supply, according to the standards of food supply per capita and the ratio of food stock to consumption (Chen,

2014). However, an increased demand for protein has impacted agricultural policy, resulting in increased food trade in soybeans and meats (Chen, 2014). While the

Chinese general public’s dietary habits changed over time, more proteins (meats, milk, and eggs) would be required in the markets (Ho, 2014).

In the Republic of Korea the agricultural industry had been highly protected by the government until the agreement with trade liberalization was put into place (Beghin,

Bureau, & Park, 2003). The Republic of Korea has become “a major importer of oilseeds and coarse grains” (Beghin et al., 2003, p. 618) since the agreement of trade liberalization. Food self-sufficiency rate, a critical food security index, is measured by the ratio of local food production divided by the required food consumption of the population (International Food Policy Research Institute, 2010). Huang (2011) translated the Korea Rural Economic Institute’s (KREI) publication about the situation

and solutions to low food self-sufficiency rate in the Republic of Korea (KREI, 2010).

The KREI, which is a national research institute established under the Prime Minister's

Office of the Republic of Korea, identified the crisis of low food self-sufficiency and has set a target food self-sufficiency rate of 47% by 2015 (Huang, 2011). However, the food self-sufficiency rate, weighted by calories, in the Republic of Korea was 44% in 2007

(Huang, 2011). Due to the Free Trade Agreement (FTA), the unstable price in the international cereal market and the change in domestic supply and demand have impacted government policy in the Republic of Korea (Huang, 2011). Although pressure from exporting has negatively impacted the domestic Korean economy, food prices and labor costs have increased, and the Korean government has considered food security to be of greater importance than trading issues. High governmental support and high tariffs for domestic market protection have been enacted (Beghin et al., 2003).

The negative impacts of the agricultural industry in Japan have been addressed by the Ministry of Agriculture, Forestry and Fisheries of Japan (MAFF), due to the negotiation of participation in the Trans-Pacific Partnership and FTA (Lin & Li, 2013).

Under such a circumstance of increased trade liberalization, the foreseen policy reform has been projected to improve the food self-sufficiency rate, revive domestic agricultural production and rural society, and establish sustainable agricultural systems (Chang,

2011). The food self-sufficiency rate in Japan was 39% in 2014, and Japan was considered one of the largest food importers in the world (Japan’s food self-sufficiency rate fails to meet lowered 45% target, 2015). The results of high food imports have included changes in consumption and dietary habits, smaller farming systems, older farmers, fewer young farm laborers, fewer farm lands, and increased fallow lands

(MAFF, 2010). The food self-sufficiency rate was expected to increase to 50% by 2020 by utilizing local production and resources, improving domestic tourism and export marketing strategies, improving rural and urban exchange and revival programs, expanding reusable energy sources, developing agricultural programs for environmental protection, developing cooperative programs in social welfare and the agricultural industry, enhancing citizen engagement in development programs, and protecting national food security (MAFF, 2010).

Global Trading Policies

Global trade, also known as international trade, is “an exchange of goods or services across national jurisdictions. Inbound trade is defined as imports and outbound trade is defined as exports” (Rodrigue, 2013, para. 2). Since countries have been unable to produce everything they need or want, trade has provided the opportunity to sell what is produced in a nation and purchase what is not produced (Rodrigue, 2013).

The World Trade Organization (WTO) was established in 1995 as an organization for trade supervision and liberalization internationally (WTO, 2014). According to the WTO

(2014), “the WTO — is the international organization whose primary purpose is to open trade for the benefit of all” (para. 1). The main activities of the WTO have included:

1. Negotiating the reduction or elimination of obstacles to trade (import tariffs, other barriers to trade) and agreeing on rules governing the conduct of international trade (e.g. antidumping, subsidies, product standards, etc.); 2. Administering and monitoring the application of the WTO's agreed rules for trade in goods, trade in services, and trade-related intellectual property rights; 3. Monitoring and reviewing the trade policies of [its] members, as well as ensuring transparency of regional and bilateral trade agreements; 4. Settling disputes among our members regarding the interpretation and application of the agreements; 5. Building [the] capacity of developing country government officials in international trade matters;

6. Assisting the process of accession of some 30 countries who are not yet members of the organization; 7. Conducting economic research and collecting and disseminating trade data in support of the WTO's other main activities; [and] 8. Explaining to and educating the public about the WTO, its mission and its activities. (WTO, 2014, para. 5)

Benefits

The benefits of international trade can be traced back to the seminal work of

Adam Smith (1776) and David Ricardo (1817). International trade can provide advantages, such as simplifying national production to a smaller number of goods, reducing production costs, improving production efficiency, increasing the quantity of shared goods, enlarging export markets, and increasing economic competition, which can lead to further improvement of products (Peng, 2011; Rodrigue, 2013).

Impacts

The competition between trading countries can also lead to numerous negative impacts. Comparative advantages have formed during times of competition, causing exploitation of weaker components of the trade members (Rodrigue, 2013). In the WTO setting, the developed country members have dominated negotiations with other members, typically leading to a result that has been more beneficial to them (Chand &

Phillip, 2001). As a result, the unfair trading competition between the rich countries and poor countries played a role in the food price crisis in 2008 (McMichael, 2009; Pritchard,

2009). Although Taiwan has been considered a developed country, its national identity in its status of independence has caused it to become a weak member in WTO (Tung,

2005). Therefore, Taiwan’s trade marketing strategies, including agricultural products, have been strongly negatively impacted by the decisions made by the leading countries

(Peng, 2011).

Agriculture in Taiwan

Agriculture has been considered the root of the economy in Taiwan and has provided “functions beyond production - it provides the food we eat, conserves the environment we live in, and is a force for social stability” (Sun, 2012, p. 1). The diverse geographical features of Taiwan have played an important role in agriculture. The majority of farm lands have been located in plain areas in the central and southern regions of the island (Agriculture and Food Agency, Council of Agriculture, Executive

Yuan [AFACAEY], 2012a). Due to the location of the island, with the Tropic of Cancer laying across the center of Taiwan, subtropical crops have been primarily produced, and tropical crops have been produced in the southern region (AFACAEY, 2014). Moreover, as a volcanic island, orogeny has created large-scale high altitude mountains in Taiwan at the central part of the island and a favorable climate to produce temperate crops

(Chang, 2015). This unique environment has allowed crops to be produced year round and a variety of crops can be produced in different seasons and regions (AFACAEY,

2014).

History Background

The agricultural industry in Taiwan has been strongly impacted by the colonial history. According to Wu’s publication, “History of Taiwan’s Agriculture” (1993), agricultural development in Taiwan can be separated into seven stages: primitive stage, pre-Dutch stage, Dutch-governed stage, Cheng-governed stage, Ching Dynasty stage,

Japan-colonized stage, and Republic of China-governed stage.

The primitive stage of agriculture can be traced back to 2000 B.C. with rice found in archaeological excavation as evidence of crop cultivation. In the pre-Dutch stage, which was before early 17th century, Chinese migrants contributed to the land

reclamation for crop cultivation of grains, sugarcane, vegetables, and fruits. During the

Dutch-governed stage in the 17th century, agriculture in Taiwan became industrialized by introducing a large amount of Chinese immigrants that settled in Taiwan for sugarcane and rice cultivation in the central and southern regions. Other than sugarcane and rice, more varieties of crops were cultivated by using the native species, species introduced from China, and species introduced by the Dutch. The Cheng- governed stage began after the Dutch were defeated by Cheng’s troops in the 1660s. In this stage, more Chinese immigrants arrived in Taiwan, with Cheng’s government and troops, leading agriculture in Taiwan to focus on military food production. More vegetable varieties were introduced in this stage, but rice was still the major crop produced (Wu, 1993).

After Cheng’s troops lost the war with the Ching Dynasty, the Ching Dynasty stage began in the late 17th century. Rice and sugarcane were the major crops at the beginning of this stage, and the key production crops gradually shifted to sugarcane, tea, and camphor for export needs. In this stage, even more Chinese immigrants settled in Taiwan and distributed across the entire island. The water conservancy systems had been widely established for agricultural production and further improved the industry

(Wu, 1993).

Taiwan entered a modernized agriculture era since the Japan-colonized stage in

1895. Taiwan was colonialized as an agricultural production source to support Japan.

Technologies and research were introduced to Taiwan to improve production, primarily in sugarcane and rice. Fruit crops, such as banana, pineapple, and citrus were also largely grown to meet the needs in Japan. After Japan was defeated in the WWII,

Taiwan was returned to the Republic of China government. The agricultural industry has been rebuilt since the 1940s and has played a fundamental role during the economic development era of the country in the 1950s, providing sufficient food and jobs to the people. More modern agricultural technologies were introduced to increase the production, but the export markets for rice and sugar decreased rapidly, which forced production to shift to asparagus and mushrooms (Wu, 1993).

After the late 1960s, the development of business and manufacturing industries began to outcompete the agricultural industry in Taiwan. Farmers confronted difficulties, such as decrease in farming labor, increase in farming labor cost, increase in farming materials and equipment, destabilization of agricultural product prices, decrease of agricultural profit, and increase of imported agricultural products, leading to a severe decline of the agricultural industry. The interaction between modern history and geographical features have caused huge impacts on today’s agricultural industry in

Taiwan. On the other hand, the long history of Chinese immigrants has been another important factor shaping the current agricultural industry and society as a whole

(Thompson, 1984).

Current Industry

The agricultural system in Taiwan is a small-farm system. The average owned farm area is 1.1 hectares (ha) per farmer, but 53% of the farmers own farm lands ranging from 0.1 to 0.5 ha (Council of Agriculture, Executive Yuan [COAEY], 2014a). In

2012, the total revenue of agriculture in Taiwan was $16 billion dollars, and 47% of the revenue was derived from crop production. Within the revenue of crop production in

2012, rice production accounted for 18%, vegetable production accounted for 28%, and fruit production accounted for 35% of the revenue (COAEY, 2014a). Agriculture land

use in Taiwan in 2012 was 803,000 ha of arable land, which was comprised of 400,000 ha as paddy fields and 403,000 ha as dry lands (COAEY, 2014a). The statistics in 2012 indicated the farm labor in Taiwan was 2.9 million people, and the revenue per agricultural household was $33,000 in U.S. Dollar per year (COAEY, 2014a). Huang,

Fu, and Chang (2009) indicated that agriculture provided 5.3% of the total employment and generated 1.5% of the gross domestic product (GDP).

Rice has been the most important cereal crop in Taiwan and was cultivated in

64% of the paddy fields with 1.3 million tons of brown rice produced, according to the statistics in 2012 (AFACAEY, 2014). Vegetable production included more than 100 vegetable crops cultivated on 143,000 ha of land in Taiwan, producing about $2 billion of value in 2012 (AFACAEY, 2014). The major vegetable crops by yield in weight in

2012 were head cabbage, bamboo shoots, watermelons, tomatoes, carrots, green onions, and loose cabbage (COAEY, 2014b). The produced vegetables have been marketed to the domestic markets, with “vegetable soybean, spinach, head lettuce, short-term leafy vegetables, melons and mushrooms [as] vegetables in high daily demand by the consumers” (AFACAEY, 2014, para. 2) and in export markets to the neighboring countries, such as China, Japan, Korea, Philippine, Singapore, and

Indonesia (AFACAEY, 2012b). The fruit industry produced more than 30 types of fruit crops from about 190,000 ha of farming acreage for 2.6 million tons of yield, which was valued at about $3 billion dollars in 2012 (AFACAEY, 2014). The fruit crops with leading yields were citrus, pineapples, bananas, guavas, mangos, papayas, and Asian pears

(COAEY, 2014b). Fruit production has been mainly sold to the domestic markets, but has also been shipped to China, Japan, Singapore, Philippine, Malaysia, and other

countries (AFACAEY, 2012b). Although the production area for flower crops was only

13,000 ha, it produced more than $0.5 billion dollars of value in 2012 (AFACAEY,

2014). The major flower crops have included Phalaenopsis, Oncidium, Anthurium,

Prairie Gentian, spray-type chrysanthemum, and oriental orchid primarily grown for export (AFACAEY, 2014).

Current Problems

According to the COAEY (2009), aging farmers has been one of the most important problems in Taiwan’s agriculture. The average age of farmers was 61 in 2009, and the number has been increasing by 10 years every 20 years. However, the shortage of agricultural labor has been another issue and has delayed the retirement of old farmers, because the younger generation has been moving out of rural areas

(COAEY, 2009).

In 2002, Taiwan received membership in the World Trade Organization (WTO).

Engagement in global trading policies has severely impacted the agricultural industry in

Taiwan (Luo & Huang, 2003). Due to the small farm system, the impacts caused by

WTO accession to the farmers and governmental administrative organizations have led to less efficiency, more difficulty in adapting and transforming to the new environment, lower prices for agricultural products, and increased difficulty in shaping government policy (Luo & Huang, 2003). Increased imports due to the membership policy in WTO have also led to a gradual change in people’s dietary habits, with increased meat uptake (Peng, 2011; Tseng, 2012). The open access for food imports after the WTO accession, plus improper agricultural policy, which encouraged farmers to set aside farming lands during 2000 to 2008, led to an increase in fallow lands by more than

200,000 ha (Tseng, 2012). Currently, the rate of agricultural imports has increased

much more than the rate of agricultural exports, which has caused local products to go unsold (Huang et al., 2009).

In 2012, the food self-sufficiency rate by calories in Taiwan was 33%, with only

270,000 ha of land for agricultural use, whereas the minimum amount of land for agricultural use to fully support the whole population in Taiwan without food import has been estimated to be 710,000 ha (COAEY, 2014a; Ministry of Foreign Affairs, 2013).

These numbers indicated a crisis in agriculture in Taiwan in terms of the sustainability of the industry and hunger in the future if the access to food imports is disabled.

Chang (2002) indicated climate change may also be a potential threat to

Taiwan’s agriculture and said, “Society as a whole would not suffer from warming, but a precipitation increase may be devastating to farmers” (p. 51). The adverse effects regarding precipitation may be caused by increased frequency of typhoon strikes and increased strength and frequency of heavy rainfall (Chen et al., 2011). The impact of climate change may also interact with the geographical altitude in Taiwan and negatively affect highland agricultural production (Chang, 2012).

Food Insecurity in Taiwan

Food insecurity has not been widely acknowledged by the general public in

Taiwan because people have still had access to food. Therefore, limited actions have been taken to address food insecurity (Peng, 2011). However, the low food self- sufficiency rate in Taiwan has indicated that the majority of food has been from imports

(Peng, 2011; Tseng, 2012), and such a reliance of imported food has caused severe food shortages in most developing countries (Schmidhuber & Tubiello, 2007).

According to COAEY (2014a), the food self-sufficiency rate in Taiwan was 68% in terms of price and 33% in terms of calories in 2012. The per capita food available for

consumption in 2012 was 40% in terms of price and 27% in terms of calories for cereals, 107% in terms of price and calories for rice, 84% in terms of price and 88% in terms of calories for vegetables, 86% in terms of price and 88% in terms of calories for fruits, 69% in terms of price and 83% in terms of calories for meats, 100% in terms of price and calories for eggs, 124% in terms of price and 153% in terms of calories for seafood, and 33% in terms of price and calories for milk (COAEY, 2014a). In all the listed categories of food, only rice, seafood, and eggs have been sufficiently produced in Taiwan, while the production of cereals, vegetables, fruits, meats, and milk has been insufficient to support the consumption of Taiwan’s 23 million people (COAEY, 2014a).

In 2012, food imports by food categories were 85% of cereals, 16% of vegetables, 16% of fruits, 17% of meats, 1% of eggs, 45% of seafood, 67% of milk, and 51% of fat consumption (COAEY, 2014a).

Causes of Food Insecurity

The United Nations Economic and Social Commission for Asia and the Pacific

(UNESCAP, 2009) has listed several causes for national food insecurity, including increases in demand, security through trade, food policies of developed countries, market-based food insecurity, food absorption and utilization, food price crises, the adverse impact of high oil prices, productivity deceleration, and speculation. In Taiwan, the causes of food insecurity have included population increases, alteration in dietary habits, fallow land increases, and reduction in production due to trading policies (Peng,

2011). The reliance of food imports has also caused fluctuations in food prices and has negatively impacted the markets (Peng, 2011).

Kuo (2013) identified the cause of Taiwan’s food security by tracing the history of modern agricultural industry. The agricultural industry in Taiwan has been suppressed

by government policy to support industrial and commercial business. By legislating flawed agricultural regulations and policies, the commercialized industry has caused adverse impacts on the environment, human health, and communities, leading to a less sustainable environment and society (Kuo, 2013).

Tsai (2010) discussed how food insecurity in Taiwan has increased due to the alteration of dietary habits. People’s dietary habits have been changing for years, due to westernization, in addition to the increase of double-salary households and high- pressure labor environments (Tsai, 2010). Although the typical staple food in Taiwan has been rice, wheat consumption in Taiwan bypassed rice consumption in 2009.

However, wheat production in Taiwan has been minimal, which has meant that almost all wheat consumed has been imported (AFACAEY, 2012a). The change of dietary habits has also led to an increased uptake of protein, but cereal production for animal feed (particularly for swine and poultry) has also been minimal. As a result, even though the self-sufficiency rate for pork and chicken has been high, 90% of the feed for swine and poultry has been from imported cereals (Tsai, 2010).

According to the definition of food security (World Food Summit, 1996), food safety can be another aspect that may negatively impact food security in a country.

Food safety has been a critical issue heavily impacting the entire society in Taiwan in recent years (Hsieh, 2015; Wei, Lo, & Lu, 2010). Tainted foods from import or produced from some major manufacturers in Taiwan have been disclosed and reported by media

(Wei et al., 2010). Food items influenced by tainted ingredients included soybean products, powdered milk, beef, beverages, breads, and cooking oil (Shih, 2014; Wei et al., 2010). Although government has implemented new policies to manage and control

the issues, public concerns and distrust about the food system have led to a food insecurity issue (Hsieh, 2015).

Conflict with Government Policy

After the accession in WTO in 2002, the direction of Taiwan’s governmental agricultural policies changed for better adapting to the open trade environment (Luo &

Huang, 2003). The current direction of government agricultural policies has included structural policy for land use reform; the improvement of crop and food production efficiency, safety, and quality; an increase in the self-sufficiency for rice and corn for feed; rational use of fertilizers; improved trade environment and industry competitiveness; renewed agricultural resources; an improved sustainable agriecosystem; and improved farmers’ education levels and welfare policy (COAEY,

2014c; Huang et al., 2009).

Although food security has been included in the government agricultural policies, some policies have been widely debated. The fallow land policy was implemented in

1990 to compensate the open access of food import in order to balance the amount of food from the local industry and imports (Kuo, 2013). The COAEY began the implementation of the “Fallow Land Reactivation Project” in 2013 to improve the self- sufficiency rate (AFACAEY, 2012b). However, Kuo (2013) indicated that the project was designed and released in a rush without comprehensive investigation. Although the goals for the project were to improve the revenue of small farmers and recover the agricultural environment, problems, such as crop planting regulation for types and volumes, seed source regulation, and access to farming materials and equipment, were not investigated, which may lead to uncertainty of the effectiveness of the results (Kuo,

2013).

The land use policy in Taiwan has also been criticized recently by the researchers and the general public (Chung & Hsieh, 2010; Hsu, 2010). A recent outbreak of conflict between the local government and rural community was the Dapu incident in June 2010. The Miaoli county government destroyed the rice lands which were almost ready for harvest in Dapu Village, according to the Land Expropriation Act, to expropriate the farm lands for industry complex construction (Kuan, 2010). In July

2010 and August 2013, the Taiwan Rural Front, a non-profit organization formed by social networkers who care about the sustainability of rural communities, organized protests with Dapu villagers and the general public against the government’s abuse of eminent domain (Hsieh, 2011; Hu, 2013). Researchers involved in the protests indicated the need for a legislation amendment to update land policies, better adapt the current social environment, and include an investigation and evaluation process and system (Hung, 2013).

Impacts to the Local Agricultural Industry

The improvement of agricultural policies in the Taiwanese government has been hindered by striving for participation in the WTO, which required an open market for food imports (Tsai, 2011). The production cost of the small farm system has been higher than large-scale farm systems and has led to higher product prices (Peng, 2011).

As a result, locally produced food in Taiwan has difficulty competing with imported food in the market. Furthermore, the competition with imported food has also led to a decline of the local agricultural industry (Tsai, 2011).

Since the beginning of the fallow land policy, the farmers who set aside fallow lands have gradually fallen behind in farm management and farming techniques. This has led to the loss of related business, such as nurseries and subcontract farm labor

(Kuo, 2013; Peng, 2011). Due to the decline in agricultural businesses, the government reassessed the policy direction in order to revive the agricultural industry (Luo & Huang,

2003). Transformation of the rural agricultural community has been pinpointed as a policy direction to improve the profitability of agricultural industry and sustain rural communities (Luo & Huang, 2003). In 2014, the annual administrative program of the

COAEY stated the need to construct new marketing strategies for domestic agricultural production and local food (e.g., branding, labeling, local eating, etc.) and to adjust farming systems by developing conservation and management projects, reorganizing farm land settings, and cultivating crop types (COAEY, 2014d).

Chang (2014) indicated the local agricultural industry has been impacted by government policies of the Cross-straits Economic Cooperation Framework Agreement

(CECFA) with China and the Strategic Economic Development District Act (SEDDA).

Concerns from the general public and growers came from the potential openness of transportation and storage business to China, according to the CECFA. The general public and growers perceived the approval of the CECFA could lead to the increased possibility of China-produced agricultural ingredients outcompeting the local industry in

Taiwan. In addition, the SEDDA allowed processed food manufacturers and exporters to use China-produced processing ingredients that cost less rather than locally produced ingredients (Chang, 2014; Hsu, 2014). Researchers have also criticized a lack of supporting measures from the government to address the negative impacts the

SEDDA could have on the local agricultural industry (Yang, 2014).

Impacts to Local Consumers

Due to the high wealth status of the majority of the Taiwanese population, people have been used to consuming imported food and perceive that they have enough

money to purchase food without boundaries (Peng, 2011). According to the theory of supply and demand, when the food supply decreases, the deficient quantity of food in the market will lead to price increases (Kuo, 2013; Peng, 2011). However, in some cases, the government has adjusted the market supply of food in order to control the market price by switching to imported food. As a result, the reliance on food imports has not changed, but the national debt has continued to increase (Peng, 2011).

Other than the impact to the market, food insecurity has also affected government policy for the consumers. Governmental food security related acts have included the promotion of rice consumption, development of local food/gourmet festivals using local food, development of new products using locally produced ingredients, encouragement of alternative dietary habits by consuming local food, and improvement of consumer education programs (COAEY, 2011).

Social justice has caught Taiwanese consumers’ attention in recent years to combat the negative effects of free trade (Wei, 2011). A green revolution has emerged in Taiwanese consumers’ purchasing behavior in that most of them are willing to pay more to support products with fair trade certification or from vulnerable groups (Wei,

2011). Chang (2009) also indicated an increased consumers’ awareness of environmental protection in Taiwan. Organizations established by consumers with similar perceptions and attitudes toward consumption behaviors have played an important role in the community (Chang, 2009). Such a collective green consumption movement in an organization reflected consumers’ care and responsibility toward environmental sustainability, the agricultural industry, and the country (Chang, 2009).

Agricultural Extension in Taiwan

History

The current public agricultural extension system in Taiwan was established by the Joint Commission on Rural Reconstruction (JCRR) after World War II (Chen, 1994).

The JCRR was established based on the Economic Aid Agreement between the

Republic of China and the United States of America signed in 1948. The goal of the

JCRR was to reconstruct agriculture after the war (COAEY, 2015). In 1950, the JCRR invited Dr. W. A. Anderson as a consultant to facilitate the process of agriculture reconstruction in Taiwan (Chen, 1994). Various American experts in extension education had been invited and engaged in the agriculture reconstruction process in

Taiwan. The experts brought the concept of the Cooperative Extension Service to

Taiwan and established the base of the Taiwan agricultural extension system, including the areas of 4-H, farmer education and communication, and household economy (Chen,

1994). In the 1960s, the Taiwan government had approved policies associated with the implementation of agricultural extension services, and sponsored and developed the extension education and research programs in the universities with agricultural programs (Chen, 1994).

The JCRR’s cooperation with the U.S. was terminated in 1978 and the organization was reorganized into the Council for Agricultural Planning and

Development (CAPD) under the Executive Yuan (COAEY, 2015). Instead of cooperating with the foreign experts, the CAPD relied on domestic experts who had worked under the JCRR (COAEY, 2015), while the extension service was assigned as a department under the CAPD (Chen, 1994). In 1984, the CAPD was further reorganized into the Council for Agriculture (COAEY, 2015) and the extension service was assigned

to the Agricultural Extension Section in the Department of Counseling (Chen, 1994).

Overall, the public agricultural extension system in Taiwan was mainly governed by the

Council for Agriculture (Chen, 1994).

System

The agricultural extension system in Taiwan was described by Rivera, Qamar, and Crowder (2001) as a pluralistic system involving partnership and power sharing.

The structure of the extension system in Taiwan has been a “dual authority structure . . . with power shared . . . between the government and a subnational governmental entity

(e.g., a state or prefecture)” (Rivera et al., 2001, p. 29), while it also has equally involved partnerships with farmers’ associations (Rivera et al., 2001). According to

Hsiao (2012), the extension services in Taiwan have been delivered by farmers’ associations, while funding, technology, and professionals have been provided by the subnational governmental entities, such as the Agricultural Research Institute, colleges and universities associated with agriculture, and central governmental agricultural institutes and agencies. As for farmers’ associations, Chiu (2003) indicated they are organized in three levels: provincial level, county/city level, and town/township level. All three levels of farmers’ associations have provided extension services through cooperation with the District Agricultural Improvement Stations and professors in colleges of agriculture specialized in extension, while they have also been supervised by each associated level of the government (Chiu, 2003). The higher the level of the governmental supervisory agency is, the larger scope of agriculture issues it views

(Chiu, 2003). However, the initiation, planning, and development of the agricultural extension education programs have been generally the duty of the Division of

Agricultural Extension at the town/township level (Chiu, 2003).

Services

In the beginning stage of Taiwan’s extension, the service foci were on farmers’ agricultural education, 4-H, and household economic education with the primary audiences of farmers, women, and youth in rural areas (Hsiao, 2012). The emphases of the extension services have been transferred to technology transform, organizational development, administrative counseling, and communication and marketing to align with the needs of the rural communities (Hsiao, 2012). The services provided by extension have been primarily funded by each level of the government and the net profits of the farmers’ associations from the previous year (Chiu, 2003). The research from the colleges of agriculture, the District Agricultural Improvement Stations, and the

Agricultural Experiment Institutes have been used as the basis of the extension services

(Chiu, 2003). The professors in the colleges of agriculture have typically provided advisory services to clients through lectures, visits, technical services, group discussions, and answer-by-phone services about required new skills, knowledge, and concepts (Chiu, 2003). For the District Agricultural Improvement Stations and the

Agricultural Experiment Institutes, their major roles have been to provide technical support to the extension services (Chiu, 2003). Therefore, the extension agent’s role has been primarily played by the specialists in the District Agricultural Improvement

Stations and the Agricultural Experiment Institutes to provide assistance to the farmers’ associations (Chiu, 2003). The services provided by the farmers’ associations have been localized based on the township and are membership-oriented only allowing members to receive services (Chiu, 2003). However, according to Tung (2001),

Taiwan’s public extension services have been focused on producers, while the consumer aspect have been overlooked. In recent years, an increasing amount of

nonprofit organizations have become involved in extension education focusing on consumers, whereas minimal effort has been made by the public extension sectors to address consumer education (Tung, 2001).

Statement of the Problem

Due to an increasing population both in Taiwan and across the globe, competition for food resources will grow (Peng, 2011; Tsai, 2011). Unfortunately, food insecurity has not been widely acknowledged by the general public in Taiwan because people still have access to food. As a result, limited action has been taken to address

Taiwan’s food insecurity issues (Peng, 2011). Therefore, the reliance on food imports in

Taiwan has become a serious national concern. Locally grown foods may help alleviate these problems, but consumers’ support of local agriculture is undocumented and believed to be low.

Purpose and Objectives

The purpose of this study was to establish a predictive model of Taiwanese general public’s support of locally grown food using their opinions about food insecurity issues in Taiwan and locally grown food.

The specific objectives of this study were to:

1. Identify Taiwanese general public’s demographics;

2. Identify Taiwanese general public’s levels of knowledge, past experience, and awareness of food insecurity issues;

3. Identify Taiwanese general public’s (a) attitudes toward Taiwan’s locally grown food and importance of agriculture, (b) perceptions of the social pressure to make locally grown food purchases, (c) perceptions of availability, affordability, and accessibility of locally grown food, and (d) intention to purchase locally grown food;

4. Determine the relationships between Taiwanese general public’s (a) knowledge, past experience, and awareness of food insecurity issues, (b) attitudes toward

Taiwan’s locally grown food, (c) perceptions of the social pressure to make locally grown food purchases, (d) perceptions of availability, affordability, and accessibility of locally grown food, (e) intention to purchase locally grown food, and (f) demographic characteristics; and

5. Determine if Taiwanese general public’s (a) knowledge, past experience, and awareness of food insecurity issues, in combination with their (b) demographic characteristics, (c) attitudes toward Taiwan’s locally grown food, (d) perceptions of the social pressure to make locally grown food purchases, and (e) perceptions of availability, affordability, and accessibility of locally grown food predict their intention to purchase locally grown food.

Significance of the Study

The findings of this study will help to identify the information gap between the general public and the agricultural industry and will provide information for government policy makers, agricultural business owners, researchers, educators, and extension practitioners, particularly in Taiwan. Lack of official and trustworthy statistics about public awareness of the food insecurity situation in Taiwan have hindered the development of problem-solving strategies in the agricultural industry in Taiwan. By measuring the general public’s knowledge levels and perceptions of food insecurity issues and agriculture, the results will support agriculture-related educational programs to enhance the general public’s awareness of food insecurity issues and their understanding of agriculture.

Possible solutions will also be addressed in the findings to minimize the adverse impact of food insecurity and support the local agricultural industry through the food access explored and discussed in this study. Marketing strategies for agricultural produce have been declared as a major need for Taiwan’s agricultural industry by the government (COAEY, 2014d). By understanding the public’s preferences toward food purchasing, the findings will provide agricultural business owners and the government directions for future investment in marketing. Extension practitioners will be able to use

the findings to establish educational programs for growers about the marketing and communication strategies that can be applied to different marketing channels (e.g., farmers markets, community supported agricultural system, etc.). The findings of this study will also lay a foundation for future research on more problem-solving strategies for food insecurity in Taiwan and provide suggestions for other countries facing or having the potential of facing a similar situation. Ultimately, this study will contribute to sustaining the agricultural industry in Taiwan’s society by strengthening the connection between consumers and growers.

Definition of Terms

1. Attitude – “A disposition to respond favorably or unfavorable to an object, person, institution, or event” (Ajzen, 1988, p. 4). In this study, the attitudinal response was towards locally grown food.

2. Awareness – The cognitive status of having or showing realization, perception, or knowledge (Aware, n.d.). In this study, awareness was defined as correctly answering the fact questions associated with food insecurity issues which can be interpreted as actual knowledge.

3. Environmental factors – Elements existing in the environment which influence an individual’s perceived ability to successfully perform a given behavior (Bandura, 1986). In this study, environmental factors included subjective norm and perceived behavioral control of purchasing locally grown food, and knowledge, awareness, and experience of food insecurity issues.

4. Experience – The process of doing and seeing things and having things happen to you (Experience, n.d.). In this study, the definition of experience was focused on food insecurity issues in Taiwan.

5. Food insecurity – The phenomenon that “exists whenever the availability of nutritionally adequate and safe foods or the ability to acquire acceptable foods in socially acceptable ways is limited or uncertain” (Anderson, 1990, p. 1576).

6. Food security – Defined by FAO using the definition from World Food Summit (1996): “Food security exists when all people, at all times, have physical and economic access to sufficient, safe, and nutritious food that meets their dietary needs and food preferences for an active and healthy life” (para. 1).

7. Knowledge – The fact or condition of knowing something with familiarity gained through experience or association (Knowledge, n.d.). In this study, knowledge was measured with survey questions related to respondents’ perceived knowledge about food insecurity issues in Taiwan.

8. Locally grown food – Food items produced in a specific area. In this study, locally grown food is used to describe fresh food products grown and produced in Taiwan, including cereals, rice, vegetables, fruits, eggs, meats, seafood, and milk.

9. Perceived behavioral control – The ease or difficulty an individual perceives to perform a given behavior (Ajzen, 1988). In this study, perceived behavioral control was defined as the perceived availability, affordability, and accessibility to purchase locally grown food.

10. Personal factors – Elements which influence an individual’s perceived ability to perform a given behavior (Bandura, 1986). In this study, personal factors included demographic characteristics, attitudes toward locally grown food, and subjective norm and perceived behavioral control of purchasing locally grown food.

11. Rural – Defined by Taiwan’s Department of Statistics, Ministry of the Interior (DSMOI, 2015) as an area with population of at least 200 people primarily depending on agriculture for living.

12. Small farms – Farms which can produce the gross cash farm income sufficient to support the farming household for production (Wu, 2011).

13. Subjective norm – The perceived social pressure to engage or not to engage in a specific behavior (Ajzen, 1988). In this study, subjective norm was defined as the social pressure an individual perceived he/she has when making purchases of locally grown food.

14. Sustainability – An integral, systematic, and long-term goal to balance the agricultural development, ecosystem, and residents’ living (Huang & Hsieh, 2000).

15. Urban – An administrative division where the population reaches 50,000 people, population density reaches 2,591 people per square mile, and more than 60% of population engage in non-agricultural industry (DSMOI, 2015).

Assumption

The assumptions of this study were as follows:

1. The survey respondents answered the questions in an honest, truthful, and accurate manner.

2. The survey was answered by the targeted subjects once and not answered by any substitute.

3. Survey questions were developed to minimize errors, and therefore, respondents were assumed to be able to fully understand the question stems and provide reliable answers accordingly.

4. Because translation between English and Taiwan Traditional Chinese was needed for this study, the languages were assumed to be translated accurately.

5. The data adjustment strategy and post-stratification weighting methods used in this study was a sufficiently efficient approach to provide representative results reflecting the target population.

Summary

Food security has been declared as one of the most important issues worldwide, due to the global population growth (FAO, 2013; Godfray et al., 2010). Taiwan, as a heavily populated island country with limited natural resources, has faced the threat of food insecurity (Peng, 2011). The openness of global trade for agricultural products has strongly impacted the agricultural system in Taiwan, where a small farm system has been dominant (Kuo, 2013). After Taiwan’s accession in WTO in 2002, the agricultural industry severely declined and led to a drop in the food self-sufficiency rate to 33% weighted by calories in 2012 (COAEY, 2014a). Because production costs have been higher in a small farm system than large-scale farm system, product price has become higher and less favorable to price-oriented consumers who have been the majority in the markets in Taiwan (Peng, 2011). Because domestic grocery consumers have been the major buyers of locally grown food in Taiwan, the declining agricultural industry in

Taiwan will not be able to revive without consumers’ support. Therefore, this study will use food insecurity as a theme and examine Taiwanese general public’s knowledge, awareness, and experience of the food insecurity issues in Taiwan combined with their perceptions of agriculture, locally grown food, and purchase intention in order to explore

possible problem-solving strategies to support the revival of the agricultural industry in

Taiwan.

CHAPTER 2 LITERATURE REVIEW

A review of literature was conducted to examine how the general public’s intention to purchase locally grown food could be impacted by their opinions associated with locally grown food and food insecurity issues in Taiwan. In order to predict the general public’s behavioral intention of purchasing locally grown food in Taiwan, knowledge, awareness, and experiences with food insecurity issues, attitude towards locally grown food, subjective norm and perceived behavioral control of purchasing locally grown food, and reported intention of locally grown food purchases were examined to inform a complete predictive model. A conceptual model of purchasing locally grown food in Taiwan using the general public’s opinions associated with locally grown food and food insecurity issues was created by combining the Theory of Planned

Behavior (Ajzen, 1991) and the Social Cognitive Theory (Bandura, 1986). This newly created model can be used to predict the general public’s locally grown food purchasing behavior by using their cognition and experiences with food insecurity issues in Taiwan in combination with their attitude towards locally grown food, and subjective norm and perceived behavioral control of purchasing locally grown food.

Food Consumption Behaviors in Taiwan

The major fresh food access of Taiwanese consumers has included traditional markets and supermarkets (Lee, 2006). A traditional market was defined by the Ministry of Culture (2009) as a marketplace assembled by individual business owners where fresh food and other daily commodities are sold. Chu (1999) indicated that traditional markets are the primary fresh vegetable purchasing locations for urban residents in

Taiwan. The respondents in Chu’s (1999) study mentioned the major reasons they

preferred to purchase fresh vegetables at traditional markets included convenience, lower prices, better quality, and higher diversity. Lee (2006) conducted research in

Neipu of Pintung County, in the Southern Region of Taiwan, which indicated that Neipu residents were used to purchasing fresh fruit, vegetable, meat, and seafood at traditional markets, while they purchased dairy, frozen food, beverages, and other commodities at supermarkets.

Other than physical access to food purchases, virtual access to food purchases has also existed in Taiwan (Chuang, 2008; Hsu, 2000). Guo (2002) investigated office workers in three major urban areas in Taipei, Taichung, and Kaohsiung and found 7 to

12% of them were willing to purchase fresh produce online. The findings of Hsu’s (2000) study indicated that consumers chose to purchase produce online because the process was time-saving and easy to use, the prices were open to the public, and the purchased products could be shipped to their home directly. However, consumers’ willingness to use the virtual access might be reduced due to a lack of physical and visual contact with the actual products, inability to receive products immediately, concerns with the return process, and safety issues in payment (Hsu, 2000). The COAEY has promoted e- shopping access to agricultural products since the early 2000s (Shia, 2002). The results of Chuang’s (2008) study were similar to Hsu’s (2000) study, but the possible risks consumers reported were ranked as time risk (i.e., time wasted for return or replacement, time taken waiting for receiving), functional risk (i.e., receiving a defective product), financial risk (i.e., distrust of website security system), and health risk (i.e., unclearly labelled product, genetically modified product).

Consumers’ food purchasing behaviors in Taiwan have changed due to recent lifestyle changes. Increased income and life quality have led food consumers to request high quality products over quantity (Wu, 2000). Food safety issues have been catching the general public’s attention in Taiwan since the late 1990s (Chen, 1997) and have led to a rising demand for organically produced food (Tsai, Lin, Lee, & Lee, 2006). Fresh produce consumers in Taiwan have had increased concern about chemical residues on the produce’s surface (Chen, 1997; Fang, Huang, Chen, & Huang, 2001; Lai, 1999).

Therefore, the motivations for consumers to purchase organic produce have primarily included health and environmental protection (Liu & Lee, 2010).

Lai’s (1999) study in Taipei City indicated differences in decisions to purchase fresh vegetables based on consumers’ characteristics. Supermarket consumers in younger age categories with lower monthly income preferred to purchase government- certified organic vegetables, whereas those consumers in older age categories with higher monthly income preferred to purchase vegetables in low price ranges, regardless of chemical application practices during vegetable production (Lai, 1999). On the other hand, traditional market consumers preferred to purchase vegetables with governmental organic certification regardless of price (Lai, 1999). Chu (1999) compared the differences among organic vegetable consumers, hydroponic vegetable consumers, and conventionally produced vegetable consumers on their purchasing preferences.

The findings indicated that organic and hydroponic vegetable consumers both preferred to purchase vegetables with high quality, curative effects, nutritious value, and brands; while conventionally produced vegetable consumers preferred to purchase vegetables that were more convenient with a lower price, regardless of their branding concept

(Chu, 1999). A study conducted by Wang (2006) also indicated that organic produce consumers in two directly-controlled municipalities, Taipei City and Kaohsiung City, were willing to pay more for organic produce compared to conventionally produced produce. Taiwanese consumers who had a higher educational level and income level also had an increased willingness to pay 20% more for products manufactured by socially vulnerable groups (Wei, 2011).

Awareness of Food Insecurity in Taiwan

Food insecurity issues have not been deeply studied in Taiwan. Books, blog posts, and even governmental posts have been published on food insecurity issues, but a limited amount of research articles were available from academic resources. The levels of perceived knowledge, awareness, and experience with food insecurity issues in Taiwan were some of the most important factors in this study. While the Taiwanese general public has had low levels of food insecurity knowledge and awareness (Ministry of Foreign Affairs, 2013; Peng, 2011; Tsai, 2011), no statistics were found to support this statement.

Tseng and Lee (2005) studied the relationship between food security and landscape value of paddy rice farms in Taiwan using a face-to-face interview survey.

The results indicated a positive impact on respondents’ willingness to increase the tax payment for rice farm conservation when the respondents had heard about or been aware of food security issues. However, no statistics were provided about the level of respondents’ awareness of food security issues.

Cheng (2010) indicated that approximately 4% of the population in Taiwan suffered from undernourishment, while approximately 12% of the population in Taiwan was over nourished. Such a phenomenon reflected an imbalanced food distribution in

the society of Taiwan. The characteristics of people who were undernourished or over nourished were also reported by Cheng (2010). Cheng (2010) found that people who were undernourished were typically working as farmers, receiving low incomes, had more old and young family members, ate at home, consumed more staple food products, had meals planned by a housewife/househusband with a low education level, or were from a single-parent family or other socially vulnerable groups. People who were over nourished typically had the opposite characteristics when compared to those who were undernourished.

Although the general public’s awareness of food insecurity in Taiwan has not been specifically reported, various studies related to green consumption behaviors have been conducted, showing increased concerns about environmental protection and environmental sustainability in the Taiwanese people. Taiwanese consumers who are younger and have higher educational levels have been reported to have higher levels of knowledge of fair trade concepts (Wei, 2011). Farmers markets have also been introduced to Taiwan’s communities to enhance people’s awareness of environmental protection by increasing interactions between producers and consumers (Tung, 2008).

Participants of events processed through farmers markets have positively reported increased understanding of the agricultural environment and willingness to participate in similar events in the future, inviting more friends to participate in future events, and changes in consumption and environmental protection behaviors (Tung, 2008). Another study about farmers markets in Taiwan indicated that consumers could better understand and agree with the importance of agriculture on the environment through what they have learned at farmers markets (Hsu, 2011). However, Cheng (2007)

studied a recent phenomenon of modern voluntary farmers in Taiwan who decided to quit their jobs in the cities and return to the rural areas for farming. These voluntary farmers perceived farming as a lifestyle rather than a job and they also appreciated the reconnection among themselves, food, and nature through laboring as farmers (Cheng,

2007). Cheng (2007) interpreted such a phenomenon as a practice of life politics about food security and lifestyle against risks in food safety and distrust of a governmental certification system.

Attitudes toward Local Agriculture in Taiwan

Attitudes toward general local agriculture in Taiwan have been barely reported in empirical research. However, people’s attitudes toward agriculture in Taiwan have been studied in certain cases. Taiwanese consumers typically have had positive attitudes toward organic food and organic farming systems in Taiwan (Hsu, 2011; Yu, 1998), whereas some consumers have had concerns about the higher prices of organic products and the trustworthiness of the organic products available in the markets (Liu &

Lee, 2010). Although consumers’ attitudes toward governmental certification systems for organic vegetables were positive, according to Chen (1997), different results have been reported in recent research. Liu and Lee’s (2010) study reflected current people’s distrust of the government’s investigation and certification systems. Hsu (2011) indicated that consumers’ level of trustworthiness about organic produce did not affect their attitude towards supporting organic produce. Other than an uncertain attitude towards the government’s investigation and certification systems for organic food, people who have a higher consciousness of environmental protection and more positive perceived value of the environment have had more positive attitudes toward organic food products (Lin, 1998; Lin & Ting, 1999; Wang, 2013; Yu, 1998). As a result,

consumers who have had positive attitudes toward organic produce have been characterized as younger, married, having higher educational levels, having higher positions in their careers, earning higher incomes, and having children (Huang, 1998;

Lin & Ting, 1999; Liu & Lee, 2010; Yu, 1998)

A new type of agriculture was developed in Taiwan in 1989 called “leisure agriculture,” which was similar to the concepts of farm tourism and recreational farming

(Ting, 2012). Leisure agriculture was defined by COAEY as an agricultural business that uses farm landscapes, natural ecology, and environmental resources, in combination with agricultural production, agricultural development, rural culture, and the farming lifestyle to provide general public recreation, understanding of agriculture, and experiences with rural farming culture (COAEY, 2013). Leisure agriculture has caught people’s attention, including tourists and researchers. Tang (2006) indicated that residents in Chungli City (in the Northern Region of Taiwan) living in areas designed for leisure agriculture reported a positive attitude towards the leisure agricultural development program. Respondents who had positive attitudes toward the program tended to have a higher understanding of the program and higher involvement in related services (Tang, 2006; Tsui, 2002). The findings of Chiou’s (2003) study in Yilan County

(in the Northern Region of Taiwan) indicated that the tourists’ positive attitudes toward their visits at the leisure agriculture farms were stronger than negative attitudes, and such attitudes were strongly impacted by their visual impression of plants but least impacted by their experiences with activities during their tours and facilities at the farms.

Chang (2013) used mixed methods to conduct a study interviewing leisure agricultural business owners and surveying tourists of leisure agricultural farms. In the interviews

participants mentioned that leisure agriculture can be used to educate tourists about environmental protection and attract tourists by its connection with food (Chang, 2013).

The surveyed tourists indicated they had a positive attitude toward agriculture after participating in the leisure agricultural tour and learned about the history of local agricultural development and the interaction between humans and nature through farming experiences (Chang, 2013).

Many researchers have connected agriculture to food consumption. Tseng, Yan,

Chuang, and Wu (2012) conducted a study on college students majoring in geography using the intervention of an agriculture-experience course that included dietary lessons and planting and farm-visiting activities. The attending students reported that they learned the hardship farmers have and began to appreciate farmers and food (Tseng et al., 2012). Tourists and residents of a fruit festival in Zhuchi Township in Chiayi (in the

Central Region of Taiwan) reported positive attitudes toward the local agricultural industry and the event (Tai, 2011). “Green restaurants” have also played a role in green consumption in Taiwan showing people’s attempts to support environmentally friendly concepts through consumption (Chou, Wang, & Hsu, 2009). People who cared about health and environmental sustainability in Taipei, Taichung, and Kaohsiung reported a positive attitude towards consumption in green restaurants, although they may not have fully understood the meaning of “Green” or known if the restaurants were actually

“Green” (Chou et al., 2009).

Since the influence of agriculture on society has decreased over time, due to economic development in Taiwan (Wei, 1981), a gap in agricultural education has developed (Hsiao, 2012). Other than educating the general public through participating

in green consumption events, or educating non-agricultural students through an agriculture-experience course, formally educated agricultural professionals have been needed to attract the younger generation back to agriculture (COAEY, 2013). Cheng

(2011) conducted a study surveying students in a college of agriculture in a university in

Taipei. The findings indicated that the students who had a strong identity in their department tended to have positive attitudes towards the agricultural profession, and the students who had strong identity in their professions tended to have positive attitudes toward the agricultural industry (Cheng, 2011).

Perceptions of Local Food in Taiwan

Local food has been defined by the Council of Agriculture as the agricultural product consumed within a short distance from its production location. “Local” can be defined as consumed at the exact production site, the county and surrounding areas of the production site, or the nation (Chang, 2015). Hung (2013) conducted local food research focusing on food produced in Kaohsiung and surveyed consumers at farmers markets and traditional markets in Kaohsiung. The findings of the study indicated that the respondents were interested in purchasing local food and felt that local food was attractive, meaningful, and important to purchase. They also perceived that holding agriculture/food festivals and holiday markets could trigger more consumers to purchase local food produced in Kaohsiung (Hung, 2013). Wan, Huang, and Chen

(2010) conducted a survey to analyze consumers’ motivation on purchasing local food from farmers markets in Hsinchu (a county in the Northern Region of Taiwan). The findings from their study indicated that respondents had a positive attitude towards farmers market, but they perceived food safety and food price as more important factors than the production location of the food (Wan et al., 2010).

Huang (2014) conducted a study surveying people who had visited farmers’ markets in Kaohsiung, and the findings indicated that positive attitudes toward local food were formed by the consumers who had a higher level of knowledge about local food. Consumers who had positive attitudes toward local food would generate an increased willingness to purchase local food; however, their willingness to purchase local food was also influenced by the level of trustworthiness they had toward the business owner (Huang, 2014). Chang (2012) interviewed onion farmers; farmer’s associations; and production cooperatives, wholesalers, and retailers in Pintung (in the

Southern Region of Taiwan); and customers located elsewhere. A certain proportion of the participants indicated that onions produced in Taiwan were of good quality and tasted better than imported onions, although some of the participants indicated that some consumers do not care about the origin of onions and care more about their appearance (Chang, 2012). Liu, Hsu, and Chen (2013) used a telephone survey to study Taiwanese consumers’ decision-making process when purchasing beef. The findings indicated that the majority of consumers perceived country-of-origin labeling for foods as important or extremely important, and they were willing to pay a higher price for beef produced in Taiwan (Liu et al., 2013). In a study of food labeling on oysters and tea, the researchers phone interviewed the general public in Taiwan and found that 89% of respondents perceived country-of-origin labeling as important or extremely important for foods (Ou, Chern, & Liu, 2011). The respondents also indicated that they perceived oysters and tea labelled as a product of Taiwan high in food safety and they were more willing to pay a higher price for Taiwanese products (Ou et al., 2011).

Lai (2006) interviewed Taiwanese consumers who were the fruit purchasers of the families and had purchased locally produced and imported fruits. The participants indicated imported fruits were typically in good quality but more expensive, whereas locally produced fruits were inconsistent in quality. The participants also indicated their decision-making on fruit purchases was strongly influenced by news rather than advertisement. Therefore, positive news, such as reporting on the health-improving effects of a certain fruit, triggered their purchase of that certain fruit, whereas negative news, such as a certain fruit had been contaminated by chemicals, hindered their purchase of that certain fruit (Lai, 2006). Moreover, participants in this qualitative study mentioned that they cared about fruit farmers and felt that wholesalers may exploit them because fruit prices did not decrease when they heard the fruit was over-produced and farmers had difficulty making a profit from the news (Lai, 2006).

The COAEY has developed localized agriculture programs, including educational programs for producers, extension agents, rural residents, youth, women, and elders, in order to improve the sustainability of the agricultural industry in Taiwan (Kuo, Ni, Chen,

Yang, Wang, & Lee, 2013). Huang, Chen, and Hsiao (2011) used mixed methods to interview researchers and experts using focus groups and surveyed extension agents to understand extension’s future strategies toward rural sustainability. The results indicated that local food development and the passing down of traditional agricultural techniques were the two most important and feasible extension missions under the vision of “Green life circle establishment” (p. 210) which was proposed by Hsiao (2008) as an integrated framework combining green resources, life network, and sustainable community (Huang et al., 2011). Ultimately, the goal of the green life circle program was

to reform and revive the rural areas by applying green production strategies, green consumption strategies, and green environment and community strategies (Hsiao,

2008; Hsiao, 2011)

Wong (2010) conducted a survey study about local dairy consumption in Taiwan, and the majority of the respondents reported they had heard about the concept of local food and were willing to support locally produced dairy. Instead of studies exploring adults’ understanding of local food, research studying children’s understanding of local food was conducted in Taiwan. Low carbon diets have been defined by the

Environmental Protection Administration (EPA, 2009) as containing foods which have minimal greenhouse gas production during their life cycle until consumption. Strategies of consuming low carbon diets have included using seasonal ingredients, using locally produced food, using food with minimal wrapping and processing, purchasing optimal quantity of food, cooking with reduced energy consumption, purchasing with reduced transportation, and reducing garbage volume (EPA, 2009). Sixth graders in Yunlin

County (in the Central Region of Taiwan) were surveyed to understand their knowledge, attitudes, and behaviors about low carbon diets (Chao, Chang, & Chen, 2013). The findings of this study indicated that the surveyed sixth graders in Yunlin County considered their support of a low carbon diet could positively impact the environment, and they would like to consume environmentally-friendly food (Chao et al., 2013).

The literature has also examined Taiwanese people’s food consumption behaviors, awareness of food insecurity situation in Taiwan, attitudes toward local agriculture, and perceptions of local food. In order to understand how to enhance the general public’s locally grown food purchases by being aware of food insecurity issues

in Taiwan, these components should be connected. To reach this goal, the theoretical framework for this study was established to examine the links connecting components, from awareness of the food insecurity situation in Taiwan to supporting locally grown food.

Theory of Planned Behavior

The Theory of Planned Behavior was first proposed in 1985 by Icek Ajzen. The theory was created based on the Theory of Reasoned Action that was proposed by

Fishbein and Ajzen in 1975 (Ajzen, 1991). As a modified theory, the major difference between the Theory of Planned Behavior and the Theory of Reasoned Action is the inclusion of available resources and opportunity to achieve a certain behavior, rather than simply considering the individual’s volitional control (Ajzen, 1988). However, similar to the Theory of Reasoned Action, an individual’s intention to perform a certain behavior is also the center of the Theory of Planned Behavior (Ajzen, 1991). Behavioral beliefs, normative beliefs, and control beliefs are the three major components that shape an individual’s intention towards a behavior (Ajzen, 1991). Therefore, attitudes toward a behavior, subjective norms, and perceived behavioral control, which are influenced by behavioral beliefs, normative beliefs, and control beliefs, respectively, can be used as highly accurate predictors of an individual’s behavioral intentions (Ajzen, 1991). As a result, an individual may have an increased possibility to actually perform the certain behavior by manipulating any or all of these predictors to strengthen the individual’s behavioral intention (Ajzen, 1991). The Theory of Planned Behavior model is shown as

Figure 2-1.

Behavioral Beliefs

Behavioral beliefs are formed based on the attributes of a given behavior (Ajzen,

1991). Psychologically, people can automatically evaluate attributes of a behavior as negative or positive; therefore, attitudes toward a given behavior are formed according to the evaluation of the given behavior’s attributes (Ajzen, 1988; 1991). If performing the behavior is believed to provide favorable outcomes, an individual would form a positive attitude towards this behavior, whereas a negative attitude towards the behavior would be formed if the behavior is believed to provide unfavorable outcomes (Ajzen, 1991).

Attitude, which has an evaluative nature, cannot be observed directly, but it can be measured through responses (Ajzen, 1988; Fishbein & Ajzen, 1975). The responses of attitudes are generally categorized into cognition, affect, and conation (Ajzen, 1988).

The features of an attitude include: a directional nature (positive or negative), a predisposition towards a response, a sustainability over time once it is established, susceptibility to change, and a consistency towards a behavior (Summers, 1970).

Therefore, attitude can be seen as a function of the behavioral beliefs that an individual has regarding the particular behavior by evaluating the salient outcomes of the particular behavior (Ajzen, 1988).

Behavioral beliefs have been described as predictors of attitude towards a specific behavior (Ajzen, 1988; Fishbein & Ajzen, 1975). Although this belief-attitude relationship has been demonstrated in various studies, some studies have also criticized the relationship between attitude and behavioral beliefs. Eiser (1994) stated that an individual would have different levels of salience in beliefs at different times. This statement meant that instead of being the determinant of attitudes, behavioral beliefs may be affected by attitudes (Eiser, 1994). Moreover, Armitage and Connor (1999)

claimed that behavioral beliefs may not be used to predict attitudes. The findings of

Armitage and Connor’s (1999) study indicated that “attitudes were not consistently associated with the same antecedent [behavioral] beliefs” (p. 50).

Normative Beliefs

Normative beliefs are associated with external influences from referent individuals or groups an individual perceives as important. An individual’s beliefs associated with the external expectations towards engagement in a particular behavior exhibited by those they deem to be important are called normative beliefs (Ajzen, 1988;

Ajzen, 1991). The important referent individuals or groups can be “a person’s parents, spouse, close friends, coworkers, and, depending on the behavior involved, perhaps such experts as physicians or tax accountants” (Ajzen, 1988, p. 121). Subjective norms, as a function of normative beliefs, are typically measured “by asking respondents to rate the extent to which ‘important others’ would approve or disapprove of their performing a given behavior” (Ajzen, 1991, p. 195). Social pressure will be formed by knowing approval or disapproval towards performing the specific behavior an individual feels from those they regard as important, and, as a result, the individual will decide if he/she should engage in the specific behavior depending on the level of social pressure they feel (Ajzen, 1988). If individuals believe that their important persons approve of a specific behavior, they are more likely to do so; conversely, if individuals believe that their important persons disapprove of a specific behavior, they are more likely not to do so (Ajzen, 1988).

However, normative beliefs have been declared as the weakest predictor of a given behavior in the theory model (Terry & Hogg, 1996). Armitage and Connor (1999) indicated that self-identity may have a stronger impact on intention of a specific

behavior than the perception of a subjective norm. Self-identity, which is driven by personal internal expectations, can be used to indicate an individual’s perceived societal role, which will lead to the formation of intention to perform a given behavior (Sparks &

Shepherd, 1992). As a result, the more individuals engage in a specific behavior, the more likely they want to continue doing so, because of their need to maintain a self- concept as someone who engages in the behavior (Charng, Piliavin, & Callero, 1988;

Sparks & Shepherd, 1992). Ajzen (1991) also indicated another consideration about moral norms. In certain situations, moral obligation can outweigh social pressure and lead to a strong impact on the intention of the specific behavior.

Control Beliefs

Control beliefs represent the presence or absence of factors that may facilitate or impede the individual’s performance of a specific behavior (Ajzen, 2002). According to

Ajzen (1991):

Control beliefs may be based in part on past experience with the behavior, but they will usually also be influenced by second-hand information about the behavior, by the experiences of acquaintances and friends, and by other factors that increase or reduce the perceived difficulty of performing the behavior. (p. 196)

By collecting information on their own ability, available resources and opportunity to perform the specific behavior, an individual forms control beliefs around a specific behavior (Ajzen, 1988; Ajzen, 1991). The individual then evaluates the ease or difficulty of controlling the available resources and the opportunity to perform the behavior, and this evaluation forms the perceived behavior control (Ajzen, 1988). Perceived behavior control, as described by Ajzen (2002), is a “subjective degree of control over performance of the behavior itself” (p. 668). The more ability, resources, and opportunity the individual perceives himself/herself to have in order to perform a specific behavior,

the stronger perceived behavior control he/she has (Ajzen, 1991). Therefore, if the individual perceives he/she has poor ability, difficulty reaching the available resources, and limited opportunities to facilitate the performance of the specific behavior, he/she will be less likely to engage in the behavior (Ajzen, 1991).

As an extension of the Theory of Reasoned Action, perceived behavioral control was added to the Theory of Planned Behavior to strengthen the prediction of an individual’s behavior, using not only volitional beliefs but also non-volitional beliefs

(Ajzen, 1988; Ajzen, 2002). Bandura’s (1977) study indicated the importance of self- efficacy on behavior modification and led to the inclusion of behavioral control to the

Theory of Planned Behavior (Levy, Polman, & Marchant, 2008; Terry & O’Leary, 1995).

Perceived self-efficacy was defined by Bandura (1998) as “beliefs in one’s capabilities to organize and execute the courses of action required to produce given levels of attainments” (p. 624). Therefore, by addressing this component of self-efficacy, the modified theory addresses the individual’s perceived ability to perform a specific behavior, according to his/her control (Ajzen, 2002).

Intention

Intention to perform a certain behavior is the center of the Theory of Planned

Behavior (Ajzen, 1991). According to the original theoretical foundation of the Theory of

Reasoned Action (Fishbein & Ajzen, 1975), “intention may be viewed as a special case of beliefs, in which the object is always the person himself and the attribute is always a behavior” (p. 12). The Theory of Planned Behavior (Ajzen, 1991) shows how attitude, subjective norms, and perceived behavioral control influence intention leading to a given behavior. By knowing an individual’s attitude, subjective norms, and perceived behavioral control, his/her intention to perform a given behavior can be predicted

(Ajzen, 1991); in addition, the actual behavioral control can also impact an individual’s intention to perform the behavior (Ajzen, 2002).

Intention has been described as the probability a person will engage in the behavior (Fishbein & Ajzen, 1975). Ajzen (1991) described intentions more clearly as

“the motivational factors that influence a behavior; they are indications of how hard people are willing to try, of how much of an effort they are planning to exert, in order to perform the behavior” (p. 181). Moreover, intention is assumed to be an immediate antecedent of the performance of a behavior (Ajzen, 2002). Ajzen and Fishbein (1980) indicated individuals’ actions can be directly attributed to their intention to perform a behavior, and therefore, if an individual has a strong intent to perform a given behavior, he/she will be more likely to actually make it happen (Ajzen, 1991).

Behavior

In the Theory of Planned Behavior (Ajzen, 1991), a human behavior can be predicted by knowing an individual’s attitude, subjective norms, and perceived behavioral control, which are the successors of behavioral beliefs, normative beliefs, and control beliefs, respectively. However, other than the influences attitude, subjective norms, and perceived behavioral control cause on intention of the specific behavior,

Ajzen (1991) also indicated the importance of considering the actual behavioral control in making behavior prediction. Behavior achievement is typically assumed that it can be impacted by interactions between the individual’s motivation and ability (Ajzen, 1991).

Therefore, a successful performance of the behavior would depend on both the intention and actual resources and opportunity available to the individual (Ajzen, 1991).

Social Cognitive Theory

Social Cognitive Theory (SCT, Bandura, 1986) is a psychological theory that has been widely used in psychology, education, and communication. This theory has been used to explain an individual’s behavior that can be performed by observing other individuals’ behavior and the environmental aspects related to the behavior and evaluating his/her self-efficacy towards the behavior (Bandura, 1986). According to

Bandura (1986), “human function is explained in terms of a model of triadic reciprocality in which behavior, cognitive and other personal factors, and environmental events all operate as interaction determinants of each other” (p. 18). Therefore, instead of explaining human behaviors as a unidirectional process, SCT views human behaviors to be determined by bidirectional interactions among “self and society, personal factors in the form of cognitive, affective, and biological events, behavioral patterns, and environmental events” (Bandura, 2001, p. 266). In such an interactive triadic reciprocality, three major factors, behavior, cognitive and other personal factors, and environmental influence, form a mutual causality effect with each other (Bandura, 1986).

Based on Bandura’s (1986; 2001) description, the model of the Social Cognitive Theory is shown as Figure 2-2.

Bandura (1986) used the term “reciprocal determinism” (p. 22) to describe the triadic reciprocality system of SCT. The behavior, cognitive and other personal factors, and environmental influence not only interact with each other, but are also considered as determinants of each other (Bandura, 1986). All the factors can influence other factors and lead to a production of effect. However, none of these factors have an absolute and complete influence to determine the final function of the effect (Bandura,

1986). Instead, the effect of each factor can be contextual and different levels of

influence on the outcome would be identified. As Bandura described: “Particular factors are, therefore, associated with effects probablistically rather than inevitably” (p. 24). In other words, the strength of each factor in the bidirectional influences would vary depending on the situation.

To understand the function of human behavior through the triadic reciprocality of the behavior, personal, and environmental factors, five basic capabilities have been used to define the nature of persons: symbolizing capability, forethought capability, vicarious capability, self-regulatory capability, and self-reflective capability (Bandura,

1986). According to Bandura (1986), these five capacities indicate how people’s cognition works through symbols people have experienced in their life (symbolizing capability), anticipated outcome based on the symbolic activities they have experienced

(forethought capability), observation of other individuals’ behavior and the outcome of the behavior (vicarious capability), the “internal standards and self-evaluative reactions to their own actions” (p. 20) with consideration of the environmental influences (self- regulatory capability), and reflection based on judgment of their experiences and knowledge and evaluation of the situation (self-reflective capability). However, this concept can be used to describe and explain the process between cognition and behavior, while it does not promise the correctness of people’s behavior (Bandura,

1986). In addition, individuals’ personality may also influence their behavior (Bandura,

1986).

Another focus of the Social Cognitive Theory is observational learning (Bandura,

1986; 2001). Observational learning is governed by four subprocesses between the modeled events and matching behavioral pattern: attentional processes, retention

processes, production processes, and motivational processes (Bandura, 1986; 2001).

Attention processes are critical to the overall observational learning process because individuals will determine what and how much of the modeling behavior to observe

(Bandura, 1986). Factors influencing the determination of attention processes, mentioned by Bandura (2001), including cognitive skills, preconceptions, value preferences of the observers, and the salience, attractiveness, and functional value of the event itself. Retention processes involve individuals’ information transformation and restructuring. Individuals will process the information of the particular event into a symbolic form, which is representative in their memory and more likely to be recalled

(Bandura, 1986). Production processes are the transitional phase from cognition to action in observational learning that the “symbolic conceptions are translated into appropriate courses of action” (Bandura, 2001, p. 272). Individuals will compare and evaluate the conception and their capability to execute the action in the given situation

(Bandura, 1986; 2001). Motivational processes indicate individuals’ acquisition and performance of the action in the observational learning process. According to Bandura

(2001), three major incentive motivators which influence individuals’ performance of the behavior learned through experience are: direct motivator, vicarious motivator, and self- produced motivator. Therefore, individuals are more likely and motivated to perform the behavior which has better value, shows similarity in their related experiences in the past and their personal characteristics with whom they observed for behavior performance, and provides a better self-satisfying feeling and a sense of worth (Bandura, 1986;

2001). However, the compatibility between social-sanction and self-sanction may impact the formation of a behavior pattern depending on the level of differences and/or conflict

(Bandura, 1986; 2001). For example, an individual would tend to exhibit the behavior with a highly threatened social consequences in a relatively safe setting while suppressing the self-praiseworthy acts (Bandura, 2001).

Self-efficacy was defined by Bandura (1986) as “people’s judgments of their capabilities to organize and execute courses of action required to attain designated types of performance” (p. 391) and considered essential to explain the Social Cognitive

Theory. The individuals’ behavior is regulated by the internal standards they have and the self-evaluation process of the given behavior (Bandura, 1986). Individuals would consider themselves competent to perform a given behavior if they consider they have sufficient skills and self-beliefs of using the skills effectively (Bandura, 1986). In addition, individuals would also make judgments about the outcome of the behavior based on their expectation about the outcomes and then decide the course of action of the behavior (Bandura, 1986). Four information sources of self-efficacy were indicated by

Bandura (1986), including enactive attainment, vicarious experience, verbal persuasion, and physiological state. Enactive attainment is based on individuals’ authentic mastery experiences and is considered as the most influential source of efficacy information

(Bandura, 1986). Individuals’ successful experience would enhance their beliefs of self- efficacy, while the failure experiences would inhibit their beliefs of self-efficacy

(Bandura, 1986). Individuals would also refer to other similar people’s behavior performance while performing a certain behavior. Such a process involving self- evaluations about the similarity between self and the observed individuals and the behavioral events described the vicarious experience (Bandura, 1986). Individuals would consider themselves to have a better chance to succeed if the similar others they

observed achieved the goal; contrarily, if the observed similar others failed to achieve the goal even with high effort input, individuals would consider themselves less capable to achieve the goal and even less willing to make a similar level of efforts (Bandura,

1986). Verbal persuasion indicated the influence of verbal encouragement or discouragement that individuals are told to “[believe] they possess capabilities that will enable them to achieve what they seek” (Bandura, 1986, p. 400). Physiological state can also influence how individuals perceive their self-efficacy. Dysfunction in behavior performance tends to occur when individuals are in stressful or taxing situations.

Additionally, fear and emotional arousal may also lead to positive or negative impacts on individuals’ perceived self-efficacy (Bandura, 1986).

Conceptual Model of Support for Locally Grown Food in Taiwan

A conceptual model was created to describe how the general public’s opinions of food insecurity issues can be used to predict their intention to support locally grown food by purchases (Figure 2-3). This model was developed by reviewing existing literature related to the Theory of Planned Behavior (Ajzen, 1991) and the Social Cognitive

Theory (Bandura, 1986). As a result, this model can be separated into two phases: the planned behavior phase and the social cognition phase.

Planned Behavior Phase

In the Theory of Planned Behavior, three components, behavioral beliefs, normative beliefs, and control beliefs, are used to predict an individual’s behavior

(Ajzen, 1991). To measure these beliefs, attitude towards the behavior was used as the variable measuring behavioral beliefs; subjective norms was used as the variable measuring normative beliefs; and perceived behavioral control was used as the variable measuring control beliefs (Ajzen, 1991). In order to understand how likely the

Taiwanese general public would be to intent to support locally produced food by purchases, their attitudes and perceptions of locally grown food were measured in this study. The general public’ perceptions of the social pressure at making locally grown food purchases were measured to address the component of subjective norms. In addition, consumers’ perceptions regarding food insecurity, including availability, accessibility, and affordability of locally grown food, will also be measured to identify their perceived behavior control.

According to Huang’s (2014) study, consumers of the farmers markets in

Kaohsiung had positive attitudes toward local food and increased willingness to purchase local food based on their purchasing experiences at the farmers markets.

Therefore, the measurement of attitudes toward locally grown food can be supported by

Huang’s (2014) findings. The measurement of consumers’ attitudes toward the importance of agriculture was to extend the understanding of consumers’ attitudes beyond local food to the local agricultural industry. The findings of Chang’s (2013) study can support this measurement: Tourists of leisure agricultural farms reported a positive attitude toward agriculture after participating in the farm tours and receiving farming experiences. Both of these findings in the existing literature also indicated a consistency in the positive impact of experiences. As a result, such a consistency can be used to explain the components in the Social Cognitive Theory which will be elaborated in the later section of the social cognition phase.

Normative beliefs are another major component in the Theory of Planned

Behavior measured by identifying if an individual’s behavior would be influenced by considering opinions from the important others or social environment (Ajzen, 1991).

Lien and Chen (2010) conducted a study to explore consumers’ green consumption behaviors in restaurants in Taipei and Hsinchu based on the Theory of Planned

Behavior. The findings indicated that the consumers’ intention to consume in a restaurant would be influenced by their friends, government policy, green products provided by the restaurant, and environmental protectors’ information related to green consumption (Lien & Chen, 2010). Similar findings were also identified in Chang’s

(2011) study targeting consumers’ consuming intention and willingness to pay in organic restaurants in Kaohsiung, based on the Theory of Planned Behavior. Chang (2011) indicated that consumers reported higher consuming intention and willingness to pay in organic restaurants when they considered their families, friends, and colleagues’ opinions related to green consumption behaviors while making decision. Based on these studies, the influence of subjective norms is expected to affect individuals’ intention to conduct a consumption behavior. Wu and Chen (2014) used the Theory of

Planned Behavior to explore Taiwanese consumers’ green consumption behavior. The findings revealed a strong normative influence on their behavioral intention to perform green consumption behaviors from individuals’ family and friends, while family’s influence was higher than friends’ influence (Wu & Chen, 2014). Factors influencing consumers’ decision-making on organic food purchases were studies by Teng and

Wang (2015). A strong effect was found in subjective norms impacting behavioral intention to consume organic food that the individuals would consider opinions from their family, friends, media coverage, and governmental supports when making organic food purchases (Teng & Wang, 2015).

Perceived behavioral control, which represents control beliefs, was examined by measuring consumers’ perceptions of availability, accessibility, and affordability of locally produced food. The availability of locally produced food in the markets has varied, depending on the categories of food. Food imports in 2012 in Taiwan included

85% of cereals, 16% of vegetables, 16% of fruits, 17% of meats, 1% of eggs, 45% of seafood, 67% of milk, and 51% of fat (COAEY, 2014a). Liu et al. (2013) indicated that locally produced beef in Taiwan had a low availability (7%) in the markets, whereas consumers’ concerns about food safety in imported beef have rendered them willing to spend extra dollars to support locally produced beef.

In terms of accessibility, access to locally produced food in Taiwan is readily available to consumers through traditional markets, supermarkets, farmers markets, and virtual online access (Chuang, 2008; Hsu, 2000; Lee, 2006; Wan et al., 2010). As for affordability, the high wealth status for the majority of the Taiwanese population has led most people to perceive that they could afford their food purchases, regardless of food sources (Peng, 2011). However, the 4% of the population in Taiwan suffering from undernourishment as reported by Cheng (2010) were typically those with low incomes, having more old and young family members, and came from socially vulnerable groups.

Those people who have been undernourished may not be able to afford to purchase sufficient food for themselves or their household. Thus, the measurements of consumers’ perceptions of availability, accessibility, and affordability of locally produced food in this study can provide a thorough understanding of how consumers perceive they would be able to support locally grown food.

The last parts of the planned behavior phase are intention and behavior.

Intention has been indicated as the central element of the Theory of Planned Behavior

(Ajzen, 1991). By knowing the individual’s attitudes and perceived behavior control, the intention to perform a certain behavior can be predicted (Ajzen, 1991). In this study, the behavior was to support locally grown food, and therefore, the intention was the general public’s intention to purchase locally grown food. Wan et al. (2010) studied consumers’ motivation on purchasing local food from farmers markets in Hsinchu and found that respondents’ positive attitude towards farmers market enhanced their motivation to make purchases at farmers markets, whereas their perceptions of higher prices of food sold at the farmers markets negatively impacted their motivation to make purchases at farmers markets. The findings of Wan et al. (2010) reflected the impacts of individuals’ attitudes and perceptions on their motivation of a certain behavior. In this study, the intention of purchasing locally grown food was expected to have a strong and direct impact on the actual behavior of locally grown food purchasing.

A directional pathway of how the general public’s attitudes, perceptions, subjective norms, and perceived behavior control regarding locally grown food and food insecurity issues would influence their behavioral intention of purchasing locally grown food has been identified in the existing literature related to the Theory of Planned

Behavior. However, based on the Social Cognitive Theory (Bandura, 1986), the behavior may lead to a formation of experience which may regulate individuals’ cognition, including attitudes and perceptions. Therefore, the triadic reciprocality system in these major constructs will be examined to explore the regulatory effect among the personal, environmental, and behavior factors.

Social Cognition Phase

According to the Social Cognitive Theory (Bandura, 1986), three major components interact with each other to coordinate an individual’s performance of a certain behavior: personal factors, environmental factors, and behavioral factors. Due to a certain level of overlapping concepts between the Theory of Planned Behavior and the Social Cognitive Theory, each component in the Theory of Planned Behavior was assigned to the components which can be explained by the Social Cognitive Theory based on the characteristics of the components. Personal factors included components related to cognition that generated from individuals themselves; environmental factors included components that are influenced by the environment or other external factors; behavioral factors indicated the execution of a given behavior (Bandura, 1986).

Therefore, in this study, personal components, including attitudes toward locally grown food, perceptions of the social pressure to make locally grown food purchases, and perceived availability, affordability, and accessibility of locally grown food, were considered as personal factors in the social cognition phase; components associated with external influences, including perceptions of the social pressure to make locally grown food purchases, perceived availability, affordability, and accessibility of locally grown food, and perceived knowledge, awareness, and experience of food insecurity issues, were considered as environmental factors in the social cognition phase; the intention of purchasing locally grown food was considered as the behavior factor in the social cognition phase.

The Social Cognitive Theory has been frequently used in studies related to green consumption in Taiwan. Lin (2012) studied consumers in Taiwan at age 18 and higher about their green consumption behavior. The findings indicated that consumers’ self-

monitoring, self-esteem, and perceived behavior outcome regarding green consumption can positively influence their anticipated green consumption behaviors (Lin, 2012). In

Lin’s (2012) study, self-monitoring described individuals’ capability to modify their behavior based on their observation of the social cues, while self-esteem indicated individuals’ perceptions of their ability, significant, and worthiness based on their evaluation of a range of domains in the social environment. Similarly, consumers’ subjective norms was found to positively influence their green consumption behaviors in

Lu’s (2014) study in Taiwan. Consumers tended to be more motivated and willing to consume green food products if they take social views into consideration while making purchase decision (Lu, 2014). In addition, Lu (2014) indicated such an effect was moderated by relevance, availability, choice, price, trust, quality, and brand of the green food products. Yang, Tseng, Huang, and Yeh (2012) conducted a green consumption study targeting junior high school students in Yunlin County (Central Region on

Taiwan). The findings indicated that the respondents’ knowledge, attitudes, and self- efficacy were positively correlated with green consumption behaviors. In addition, the higher the respondents’ perceived self-efficacy was, the more positive their attitudes toward green consumption were; the more frequent their exposure to environmental protection information was, the better performance of their green consumption behaviors was (Yang et al., 2012).

Although the existing related studies were not directly targeting food insecurity issues or locally grown food, green consumption behavior was still an environment- related topic which may provide potential hints to this study.

Summary

This chapter included a full discussion about the major elements in this study based on the existing empirical research. Although a lack of existing research directly related to food insecurity in Taiwan was found, studies related to green consumption and sustainable agriculture were used for discussion to explore possible relationships with food insecurity issues in Taiwan. The theoretical foundation of this study, the

Theory of Planned Behavior and the Social Cognitive Theory, were discussed in depth with each critical component in the theories included. The Theory of Planned Behavior was described as an explanation of how an individual’s behavioral intention can be affected by attitudes, subjective norms, and perceived behavioral controls. Elements of the theory of planned behavior were discussed including behavioral beliefs, normative beliefs, control beliefs, and how these beliefs influence attitudes, subjective norms, and perceived behavioral control. The Social Cognitive Theory is a theory explaining how individuals’ behavior performance can be influenced by the internal factors from themselves and external factors from the environment, while also regulated by their experiences and observations of the behavior. Discussion of the Social Cognitive

Theory included the three major components in the theory: personal factors, environmental factors, and behavioral factors. The conceptual model of this study was created by merging the Theory of Planned Behavior and the Social Cognitive Theory.

Taiwanese general public’s behavior of supporting locally grown food by purchases was expected to be influenced by attitudes, subjective norms, and perceived behavioral control associated with locally grown food, which may have been impacted by their knowledge, awareness, and experience of food insecurity in Taiwan.

Figure 2-1. The model of Theory of Planned Behavior (Ajzen, 1991).

Figure 2-2. The model of Social Cognitive Theory (Bandura, 1986).

Figure 2-3. Conceptual model of support for locally grown food in Taiwan.

CHAPTER 3 RESEARCH METHODS

Overview

Food insecurity and the agricultural industry in Taiwan were discussed in the first two chapters. These chapters illustrated a lack of information about public awareness of food insecurity in Taiwan and a potential connection between people’s food insecurity awareness and behavior towards purchasing locally grown food. A conceptual model, generated by merging the Social Cognitive Theory (Bandura, 1986) and the Theory of

Planned Behavior (Ajzen, 1991) was introduced to contextualize this study. In order to meaningfully connect people’s food insecurity awareness to their consumption behavior of purchasing locally grown food, rigorous research was needed to demonstrate the existence of the connection. Therefore, the purpose of this study was to establish a predictive model of consumers’ support of locally grown food using their knowledge and awareness levels of food insecurity issues in Taiwan. The findings of this study can be used to support extension educators and practitioners in the development of educational and communication programs regarding the food insecurity issues in order to enhance people’s support of locally grown food and the agricultural industry in

Taiwan. In this chapter, the research method will be discussed, including the research design, population and sample, instrumentation, data collection, and data analysis.

Research Objectives

1. To identify Taiwanese general public’s demographics;

2. To identify Taiwanese general public’s levels of knowledge, past experience, and awareness of food insecurity issues;

3. To identify Taiwanese general public’s (a) attitudes toward Taiwan’s locally grown food and importance of agriculture, (b) perceptions of the social pressure to make

locally grown food purchases, (c) perceptions of availability, affordability, and accessibility of locally grown food, and (d) intention to purchase locally grown food;

4. To determine the relationships between Taiwanese general public’s (a) knowledge, past experience, and awareness of food insecurity issues, (b) attitudes toward Taiwan’s locally grown food, (c) perceptions of the social pressure to make locally grown food purchases, (d) perceptions of availability, affordability, and accessibility of locally grown food, (e) intention to purchase locally grown food, and (f) demographic characteristics; and

5. To determine if Taiwanese general public’s (a) knowledge, past experience, and awareness of food insecurity issues, in combination with their (b) demographic characteristics, (c) attitudes toward Taiwan’s locally grown food, (d) perceptions of the social pressure to make locally grown food purchases, and (e) perceptions of availability, affordability, and accessibility of locally grown food predict their intention to purchase locally grown food.

Research Design

This study was a descriptive-correlational study using a non-experimental web- based survey research design. In order to accomplish the research objectives, quantitative research methods were used in this study. The research was designed to identify Taiwanese consumers’ demographic characteristics, their current awareness of food insecurity issues in Taiwan, their attitudes and perceptions of locally grown food, and their intention of purchasing locally grown food. Additionally, it sought to determine the relationship between general public’s opinions of food insecurity issues and locally grown food and their intention to purchase locally grown food, and to make predictions about consumers’ locally grown food purchases using their demographic characteristics, food insecurity knowledge, awareness, and experience, and attitudes and perceptions of locally grown food. The survey instrument was developed by the researcher due to a lack of available instruments for this study. No research was found using an instrument conducting a public opinion survey focusing on locally grown food in combination with food insecurity issues in Taiwan. A web-based survey design was chosen because of its

economic feasibility to conduct a public opinion survey reaching large populations

(Dillman, Smyth, & Christian, 2009). In order to ensure the access to the respondents, the Northern Region of Taiwan was chosen as the target region. The Internet coverage rate in the Northern Region was almost 90% in 2014 (National Development Council,

2014), which also indicated that most of the population was covered by the use of an

Internet survey. Moreover, using the Northern Region as the target region may reflect the opinions of the general public living around the capital area, which is the most urbanized region with the largest population compared to other regions in the country.

Population and Sample

The population of this study was the general public living in the Northern Region of Taiwan, including Taipei City, New Taipei City, Keelung City, Taoyuan City, Hsinchu

City, Hsinchu County, and Yilan County, aged 18 and older (N = 8,690,539)

(Department of Household Registration, Minister of Interior, 2015). The map of the

Northern Region of Taiwan can be seen in Figure 3-1. This region was chosen because it covers the major capital areas and the surrounding cities and counties so that sufficient accessibility to the Internet for the survey could be ensured and diversity in population composition with immigrants from other regions of Taiwan could be covered.

The purposive sampling method was used to collect data by sampling residents living in the Northern Region aged 18 and older. The age was framed for sampling because people under 18 were considered as dependents in the households.

A non-probability opt-in sampling strategy, a sampling method which has been widely used in public opinion surveys, was used for this quantitative survey (Baker et al., 2013). Although a probability sample is more desirable when conducting research, various studies have indicated that the feasibility of non-probability sampling is

comparable to probability sampling and sometimes is even more representative than probability sampling when appropriate measures are used to adjust the data to eliminate threats to validity (Twyman, 2008; Vavreck & Rivers, 2008). The opt-in sampling, which was accomplished by using a panel via a public opinion survey company, was weighted by the proportion of sex, age, and population in each city and county. A panel approach, which is a popular approach used in online surveys by sampling “individuals who have been recruited in advance and agreed to do surveys”

(Baker et al., 2013, p. 10), was used in this study in order to ensure that enough responses were received in the limited duration of time allotted. Sampling size (n = 400) was determined by rounding up the sample size of 384 recommended by Dillman et al.

(2009) using a confidence level of 95% and a confidence interval of .05. To ensure representativeness of the population, post-stratification weighting procedures (Kalton &

Flores-Cervantes, 2003) were used ex post facto according to the demographic characteristics as shown in the 2015 census data provided by the Ministry of the

Interior. Post-stratification weighting methods were used to overcome the limitations of non-probability sampling, including non-participation, selection, and exclusion biases

(Baker et al., 2013).

Survey Error

Survey error can occur in any type of survey. Four types of survey errors, which can impact validity and reliability of the study, were identified by Dillman et al. (2009): sampling error, coverage error, measurement error, and non-response error. The use of a non-probability sampling strategy can lead to the occurrence of sampling error and coverage error.

By sampling the population instead of measuring the whole population, sampling error can occur (Ary, Jacob, & Sorensen, 2010). The quality of a sample can affect the reliability of the data. As a result, ensuring the representativeness of the sample was important. In order to reduce sampling error and maximize the representativeness of the sample, data were weighted, using post-stratification methods (Kalton & Flores-

Cervantes, 2003), based on the 2015 census statistics of the demographic characteristics received from the Ministry of Interior (2015).

Coverage error “occurs when not all members of the population have a known, nonzero chance of being included in the sample for the survey and when those who are excluded are different from those who are included on measures of interest” (Dillman et al., 2009, p. 17). In this study, coverage error was minimized by weighting data based on the census of 2015 (Ministry of the Interior, 2015) to ensure the representativeness of the sampled respondents to the population. However, the restriction of this study was that the consumers who did not have Internet access were not reachable. As a result, the findings should only be applied to consumers with Internet access.

Measurement error “occurs when a respondent’s answer is inaccurate or imprecise” (Dillman et al., 2009, p. 18). Survey questions that are poorly worded and designed can easily lead to measurement error, because survey respondents are not able to request assistance to understand the questions during the responding process

(Dillman et al., 2009). Survey results can be optimized by using items that are easy to answer to enhance the truthfulness of the responses. In order to eliminate measurement error in this study, the survey questionnaire was reviewed by two panels of experts (one reviewed the English instrument and one the Chinese instrument) and

also pilot tested to ensure the quality of the questions, both in wording and language, as well as instrument validity and reliability. However, respondents’ interpretations of the survey questions could still impact the internal validity of this study.

The last type of survey error is nonresponse error, which occurs “when the people selected for the survey who do not respond are different from those who do respond in a way that is important to the study” (Dillman et al., 2009, p. 17). The existence of nonresponse error can become a threat to external validity and impact generalizability, due to lack of observation from nonrespondents (Lindner, Murphy, &

Briers, 2001). Various methods have been recommended to address nonresponse error, including (a) ignoring the nonresponse, (b) comparing respondents to population,

(c) comparing respondents on known characteristics, (d) comparing early respondents to late respondents, (e) using “double-dip” nonrespondents, (f) using “days to respond” as a regression variable, (g) comparing respondents to nonrespondents, (h) generalizing to the respondents only, (i) assuming there is no response bias and generalizing to the population, (j) calling nonrespondents, and (k) increasing mailings or contact efforts (Israel, 1992; Lindner et al., 2001; Miller & Smith, 1983). In this study, nonresponse error was minimized by using a panel and collaborating with the survey company to ensure the quantity of required responses. Additionally, the force response option was selected in all survey questions to eliminate possible missing responses. As a result, the quality of the responses was secured, and no further process dealing with nonresponse in the collected responses was necessary.

Instrumentation

The survey instrument used for this study was created by the researcher. Online distribution was used to deliver the questionnaires to the respondents. Questionnaire

launch, distribution, response collection, and recording were performed using the platform operated by the public opinion survey company, Qualtrics.

A researcher-developed instrument was used for this study because no instrument existed that measured the variables of interest in the study associated with national food insecurity issues in Taiwan and consumers’ purchase of locally grown food. However, questions developed to measure the Theory of Planned Behavior variables (attitude, subjective norm, perceived behavioral control, and intention) were adopted and modified based on Ajzen’s (2015) questionnaire construction example,

Huang, Rumble, and Lamm’s (2014) attitude measurement, and Wang, Lin, Fang, Tu,

Chang, and Lin’s (2011) study focused on Taiwanese farmer’s engagement in organic production. Respondents’ levels of knowledge, awareness, and experiences with food insecurity issues in Taiwan, their perception about the agricultural industry and attitude, subjective norm, and perceived behavioral control associated with locally grown food, as well as their purchasing intention of locally grown food were measured using the questionnaire. The last part of the instrument identified respondents’ demographic characteristics. The entire survey instrument was developed based on the conceptual model, which was generated by combining the Social Cognitive Theory (Bandura, 1986) and the Theory of Planned Behavior (Ajzen, 1991).

The survey instrument can be seen in Appendix A for the English version and

Appendix B for the Traditional Chinese version, which is the actual instrument used for this study. To understand how the general public’s purchase of locally grown food has been impacted by their opinions associated with food insecurity issues in Taiwan, survey questions were separated into three major parts. The first part included

questions about local agriculture and locally grown food, including attitudes toward locally grown food and the importance of agriculture; perceptions of the social pressure at making locally grown food purchases (subjective norm); perceptions of the availability, accessibility, and affordability of locally grown food (perceived behavioral control); and intention to purchase locally grown food. The respondents were first asked to indicate their perceived importance of agriculture by seven statements related to the benefits of agriculture on a five-point Likert-type scale (1 = Not at All Important, 2 =

Slightly Important, 3 = Important, 4 = Very Important, 5 = Extremely Important). The definition of locally grown food was provided before asking the locally grown food related questions. Respondents’ intention to purchase locally grown food was then measured by asking the likelihoods of intending to purchase eight types of locally grown food using a five-point Likert-type scale (1 = Very Unlikely, 2 = Unlikely, 3 = Neither

Likely nor Unlikely, 4 = Likely, 5 = Very Likely). Next, the respondents were asked to indicate their attitudes toward locally grown food. A five-point semantic differential scale with eight sets of bipolar adjectives was used to measure respondents’ level of agreement between two listed bipolar adjectives (e.g., natural and unnatural, high quality and low quality, etc.). Subjective norms and perceived behavioral control were measured by asking the respondents to indicate the level of agreement or disagreement with the six listed statements in each question using a five-point Likert-type scale (1 =

Strongly Disagree, 2 = Disagree, 3 = Neither Agree nor Disagree, 4 = Agree, 5 =

Strongly Agree). In order to ensure the measurements of intention, attitude, subjective norms, and perceived behavioral control are reliable, the points of these locally grown

food related measurements were averaged to create index scores for further reliability analysis with a range from one to five.

The second part of the instrument included questions related to food insecurity in

Taiwan, covering respondents’ level of perceived knowledge, awareness, and experiences of food insecurity issues. In this part, the respondents were first asked to indicate their perceived level of knowledge using a five-point Likert-type scale with seven items associated with food insecurity issues (1 = Not at All Knowledgeable, 2 =

Slightly Knowledgeable, 3 = Somewhat Knowledgeable, 4 = Knowledgeable, 5 = Very

Knowledgeable). The awareness of food insecurity issues in Taiwan was then measured using eight true or false questions and two multiple choice questions related to the facts of the food insecurity situation in Taiwan, with truly correct answers available. The awareness scores were calculated based on the correction rate of these

10 questions. Respondents’ experience with food insecurity issues was measured using a multiple choice question where respondents were asked to select all items that applied with five food insecurity related incidents, None of Above option, and Other option. The respondents were able to indicate non-listed food insecurity issues if selecting the Other option. For respondents selecting None of Above option, the responses were treated as zero experience of food insecurity issue. Index scores of perceived knowledge, awareness, and experiences of food insecurity issues were calculated for reliability analysis as well. The index score of perceived knowledge was created by averaging the points of the responses with a range from one to five, while the index score of awareness was created by summing the number of correctly answered awareness questions with a range from zero to 10. Similar to the index score

of awareness, the index score of experience was calculated by summing the number of experienced food insecurity incidents that could range from zero to five.

Lastly, the third part of the questionnaire focused on demographics. Multiple choice questions were used to assess demographic characteristics, including sex, age, zip code, city of residence, area of residence, agricultural involvement, educational level, marital status, number of dependent children, being the decision maker of food purchase in the household, occupation, ethnicity group, personal monthly income, and political affiliation. Respondents of this study were characterized by summing the frequency of each demographic characteristic. Age and city of residence were set as the screening question at the beginning of the survey in order to screen out respondents who were not in the population of interest. Some demographic questions were asked at the beginning of the survey to ensure the respondents were qualified to answer the survey and to minimize question order influence on respondents’ responding process, including age, city of residence, zip code, area of residence, being the decision maker of food purchase in the household, and agricultural involvement. Age was identified by asking the respondents to provide their year of birth instead of actual age in order to facilitate future longitudinal studies which may use the data from this study.

Respondents indicating their year of birth later than 1997 were dropped out from the survey. Respondents were asked to provide their city of resident by selecting one of the seven cities/counties they currently live in, while None of Above was also provided as an option. Respondents choosing None of Above were sent directly to the end of the survey and disqualified to respond to the survey. Respondents’ zip code was collected by asking the respondents to provide their 3-digit zip code of their residence location in

order to confirm their city of residence. Respondents were asked to provide their area of residence by choosing the best option describing their residential location using a rural urban continuum scale with five options (A farm in rural area, Rural area, not a farm,

Urban or suburban area outside of city limits, Subdivision in a town or city, Downtown area in a city or town) (Huang et al., 2014). The respondents then indicated if they were the primary decision maker of food purchases in the household by selecting Yes or No in the question. Respondents’ agricultural involvement were asked by selecting the best option within the five options, including (a) I am involved in agriculture for a living, (b) I am involved in agriculture as a hobby, (c) I have been involved in agriculture in the past,

(d) I am not involved in agriculture, but someone in my immediate family is, and (e) I have never been involved in agriculture and no one in my immediate family has ever been involved in agriculture.

The demographic questions asked in the end of the survey included sex, educational level, occupation, marital status, number of dependent children, race, personal monthly income, and political affiliation. Respondents’ sex was measured by asking them to indicate if they are Male or Female. As for educational level, seven levels were provided for the respondents to select the highest level of education they have complete (Did not graduate high school, High school graduate, Professional school graduate, Some college, no degree, College degree, Master's degree, Doctoral degree). Respondents’ occupation was collected by asking them to select the best option within the 13 items describing their occupation, including Industrial industry,

Business, Service industry, Student, Manufacturing industry, Military, police, governmental officer, Education, research, Agricultural industry, Self-employed

profession, Housewife/househusband, Retired, Unemployed, and Other. If Other was selected, the respondents were able to provide specific answers which were not listed in the question. Respondents’ marital status was asked by selecting if they were Single,

Married, or Other. Respondents were asked to indicate if they have any dependent children to take care of in the household by selecting Yes or No. If Yes was selected, the respondents were then asked to indicate the number of dependent children in the household. Note that number of children in a household is not restricted in Taiwan

(Gender Equality Committee of the Executive Yuan, 2013), asking the number of dependent children may provide additional information to data analysis. Respondents’ race was collecting using a multiple choice question adopted and revised by the race question in Tu and Liao’s (2006) study to select all items that applied. The items of the race question included (a) Taiwan•born Taiwanese • Southern Min, (b) Taiwan•born

Taiwanese • Hakka, (c) Taiwan•born Taiwanese • Mainlander, (d) Taiwan•born

Taiwanese • Native Taiwanese, (e) Foreign•born Taiwanese, (f) Foreigner, and (g)

Other. If Other was selected, the respondents were able to provide specific answers unlisted in the question. The respondents were also asked to indicate their personal monthly income with the unit of New Taiwan Dollar (NTD) by selecting one option from the six options. The provided options included (a) Less than $10,000, (b) $10,000 •

$19,999, (c) $20,000 • $39,999, (d) $40,000 • $59,999, (e) $60,000 • $79,999, and (f)

$80,000 and more (Huang, 2014). The two income categories, Less than $10,000 and

$10,000 • $19,999, were merged into one category to standardize the intervals between each income level during data analysis. Lastly, the respondents’ political affiliation was collected by asking them to select the best option reflecting their political beliefs or

values associated with the two major political leagues (Kuomintan league as “Blue” and

Democratic Progressive Party league as “Green”) in Taiwan. Five options were provided in the political affiliation question, including a) Very supportive to the "Blue," b)

Supportive to the "Blue," c) Neither supportive to the "Blue" nor "Green," d) Supportive to the "Green," and e) Very supportive to the "Green" (Su & Fu, 2011).

The descriptive statistics generated by analyzing the survey results were used to address the first three objectives. In order to achieve objectives four and five, the relationships between variables were examined and the prediction model was developed. Therefore, dependent and independent variables were identified.

Independent Variables

The interval independent variables in this study included respondents’ (a) knowledge of food insecurity issues in Taiwan, , (b) attitudes toward locally grown food,

(c) subjective norm of purchasing locally grown food, and (d) perceived behavioral control of purchasing locally grown food. Awareness and experience of food insecurity issues in Taiwan were numerical variables. As for demographic variables, sex, city of residence, area of residence, agricultural involvement, and personal monthly income were treated as categorical variables. However, number of dependent children was recoded as having dependent children or not, and thus, it was treated as a dichotomous variable. Being the decision maker of food purchase in the household or not was also a dichotomous variable. As for age, it was recoded by transforming the year of birth into age and treated as a numerical variable.

Dependent Variables

The dependent variable in this study was intention to purchase locally grown food. This identified dependent variable was an interval variable used in the prediction

model with the independent variables listed above including (a) knowledge, (b) awareness, (c) experience of food insecurity issues in Taiwan, (d) attitudes toward locally grown food, (e) subjective norm of purchasing locally grown food, (f) perceived behavioral control of purchasing locally grown food, and (g) selected demographic variables. A series of multiple regression models were tested according to the significance and strength of impact that each independent variable had on the variation of the dependent variable, the respondents’ intention to purchase locally grown food.

Pilot Study

The developed survey questions were reviewed by two panels of experts to minimize measurement error and ensure face and construct validity prior to conducting the study. The first panel included individuals with backgrounds in food security issues, public opinion research, and survey design to validate the survey questions. However, the survey questions were reviewed by another panel consisting of one English and

Taiwan Traditional Chinese translation professional and two bilingual [English and

Taiwan Traditional Chinese] researchers, because of the need to translate the instrument between English and Mandarin Chinese.

The reviewed translated survey was first pilot-tested in September of 2015 by a small group of Taiwanese people (n = 30) living in Gainesville, Florida and fluent in

Taiwan Traditional Chinese to ensure the validity and reliability of the survey. A convenience sampling method was used in this pilot study due to time and financial limitations. The respondents were recruited from the University of Florida Taiwanese

Student Association Facebook page. The recruitment statement was described in

Taiwan Traditional Chinese to encourage the local Taiwanese community’s participation. Extra screening questions were used to ensure the eligibility of the

respondents that they were also residents of Taiwan in order to enhance the relevancy to the target population. Although the respondents may not actually make locally grown food purchase in Taiwan, they were asked to provide responses based on what they think they would be likely to do if they were in Taiwan. The survey platform operated by the survey company was used for questionnaire delivery and data collection. The survey link was publicly posted on the University of Florida Taiwanese Student

Association Facebook page to recruit volunteers to respond to the survey. While the

Facebook page was used for the survey recruitment post, the page was also used to provide timely assistance if the respondents had survey related questions, as well as to provide reminders about the need of additional responses and make announcement of survey completion when 30 complete responses were collected.

When 30 valid and complete responses were collected, 45 respondents were found that had entered the survey. Pilot test data were analyzed using SPSS® 22.0 to measure construct validity and reliability. Index scores were calculated as a composite measure by averaging or summing up the scores of multiple items developed to measure the specific elements, such as attitudes and perceptions. All the index scores of the constructs were found with reliability coefficients of Cronbach’s alpha larger than

.70 (See Table 3-1), which indicated the indices were measuring what they intended to measure (Ary et al., 2010; Kline, 1998).

Potential Validity Threats

The use of web-based surveys and non-probability sampling may lead to threats to validity for this study. According to Ary et al. (2010), threats of internal validity to a study include history, maturation, testing, instrumentation, statistical regression, selection, experimental mortality, selection-maturation interaction, experimenter effect,

subject effects, and diffusion. Since this study was not an experimental research, selection, experimental mortality, selection-maturation interaction, experimenter effect, and diffusion effect were not threats of validity in this study. A short period of time, approximately 15 minutes, used for the survey response would not involve a maturation effect and should not be affected by any extraneous event which may lead to a history effect during the survey. However, history effect may have occurred during the process of data collection which took nine days in this study. The questionnaire used in this survey study was only delivered one time and the respondents who were involved in the pilot test were excluded from the formal study, and therefore, testing effect was not a threat of validity to this study.

The major threats of internal validity in this study included instrumentation, statistical regression, and subject effects. The threat of instrumentation occurs when changes occur in the measuring instrument (Ary et al., 2010). Reviews of the instrument completed by the panels of experts ensured the face and construct validity. Moreover, the use of a survey response platform provided by the survey company also ensured the consistency of questionnaire style during the response session. Ary et al. (2010) stated that “statistical regression is a threat to internal validity when a subgroup is selected from a larger group on the basis of the subgroup’s extreme scores (high or low) on a measure” (p. 276). To address the threat of statistical regression, the instrument was pilot tested prior to being formally conducted to ensure the reliability of the variables in the instrument. Subject effects were also a threat to validity in this study because of the attitudes respondents developed during the survey response procedure

(Ary et al., 2010). In order to reduce the threat of subject effects, the questionnaire was

reviewed by a panel of experts to ensure the wording and order of the questions were properly set.

The external validity of this study was primarily influenced by the non-probability sampling method. Because the accessible population did not fully cover the target population, the results could only be generalized to the accessible population. In this study, the target population was the general public in the Northern Region of Taiwan aged 18 and older, but the accessible population was the general public in the Northern

Region of Taiwan aged 18 and older with Internet access. Therefore, when generalizing the findings to the population, only the general public in the Northern Region of Taiwan aged 18 and older with Internet access could be considered instead of all the general public in Taiwan. Additionally, survey respondents’ attitudes during the survey- responding process may also become a threat to external validity. The length of the survey, question order, and specific questions were considered to minimize adverse effects on the external validity of this study.

Reliability

The reliability of the instrument was assessed by the use of pilot study data and actual data. Cronbach’s alpha coefficient was used to determine the internal consistency of the scales. This coefficient was used “when measures have items that are not scored simply as right or wrong, such as attitude scales or essay tests” (Ary et al., 2010, p. 246) and has been frequently used by researchers as “the index of reliability” (Ary et al., 2010, p. 247). According to Nunnaly (1978), reliability is high when the coefficient is .90 or higher, moderate when the coefficient is ranged from .80 to .90, and acceptable when the coefficient is .70 to .80. Ary et al. (2010) suggested the optimal coefficient of reliability for aptitude tests designed for behavior prediction to be

.80, while Kline (1998) indicated that a reliability coefficient at .70 should be acceptable.

All the index scores of the constructs in the instrument were calculated and found reliable based on the pilot test data, as well as the actual data. The reliability coefficients of the index scores can be seen in Table 3-1.

Data Collection

Prior to the data collection procedure, the proposal of this study was submitted for approval to the University of Florida’s Institutional Review Board (UFIRB). The IRB-

02 “is responsible for reviewing and monitoring research with human subjects… involving behavioral observation/recordings … [and] surveys…” (UFIRB, 2014, para. 1).

When submitting materials to the UFIRB, information about the research, including the instrument, acknowledgement of potential benefits and risks to the participants, participant recruitment methods, and informed consent form were provided. The study was conducted after receiving approval from the UFIRB in September 2015 (Protocol

#2015-U-968, See Appendix C).

Procedure

The actual survey instrument was launched after being reviewed by the expert panels, IRB approval, and pilot testing. The questionnaires were delivered to the respondents via the Internet through a public opinion survey company, Qualtrics, between September 24th and October 2nd, 2015. An opt-in procedure was used to recruit survey respondents who were aged 18 and older and lived in the Northern

Region of Taiwan. At the end of the data collection, 991 respondents had entered the survey, resulting in a total of 419 completed responses and a participation rate of 42%.

To ensure the respondents were in the population of interest, they were asked to indicate their year of birth and city of residence at the beginning of the survey. If their

year of birth was in or before 1997 and city of residence was one of the seven listed cities/counties, respondents were then guided to answer the research questions associated with local agriculture, locally grown food, food insecurity issues, and demographics.

Once the survey was launched in the system, invitation emails were sent to the participants who were in the survey company’s panel list. The survey link was included in the invitation email and the informed consent was shown once the participants entered the survey. Participants who did not consent to participate were dropped from the system. Response rates were monitored daily by Qualtrics during the response period. When the response rate slowed down, reminders and more invitations were sent by Qualtrics to notify the respondents who had not completed the survey. The additional invitations and reminders were first sent four days after the initial launch and then everyday until the needed 400 responses were received. The survey session was closed when the required number (n = 400) of responses was received. The final flush of the responses led to the final number of responses as 419.

Data Analysis

Quantitative research methods were used in this study. The data were analyzed using SPSS® 22.0 to calculate descriptive, correlational, and regression statistics. The objectives were reached by using descriptive statistical analysis in objectives one, two and three. Inferential statistics were used to inductively predict the population using the sample for objectives four and five (Lomax & Hahs-Vaughn, 2012). Correlational statistical analysis was used in objective four, and multiple regression analysis was used in objective five. Prior to using SPSS for analysis, data were weighted ex post facto by using a post-stratification method (Kalton & Flores-Cervantes, 2003), based on

the 2015 census statistics of the demographic characteristics (sex and age) in the selected cities and counties (Ministry of the Interior, 2015). The weight coefficients can been seen in Table 3-2. After data analysis, the objectives of this study were achieved:

(a) to identify Taiwanese general public’s demographics, (b) perceived knowledge level, awareness, and experience of food insecurity issues, (c) and attitudes, subjective norm, perceived behavioral control, and intention associated with locally grown food purchases, (d) to determine the relationships between Taiwanese consumers’ demographic characteristics and their opinions of food insecurity issues and their attitude, perception, and intention to purchase locally grown food, and (e) to develop a prediction model using the general public’s demographic characteristics, opinions of food insecurity issues, and attitudes and perceptions associated with locally grown food to predict their intention to purchase locally grown food.

Descriptive Statistics

According to Lomax and Hahs-Vaughn (2012), descriptive statistics can provide summarized data from the entire dataset and describe the fashion of data. In order to identify the Taiwanese general public’s demographics (objective one); levels of perceived knowledge, awareness, and past experience of food insecurity issues

(objective two); and their attitudes toward locally grown food, perceptions of the social pressure at making locally grown food purchases (subjective norm), perceptions of availability, affordability, and accessibility of locally grown food (perceived behavioral control), and intention to purchase locally grown food (objective three), survey respondents were asked questions specifically related to each of these items.

Descriptive statistics were generated through the frequencies of each item in the questions for nominal or interval variables, including measurements for some locally

grown food related variables (subjective norm, perceived behavioral control, and intention) and food insecurity variables. For questions using semantic differential scale, items were averaged to provide descriptive statistics, including means and standard deviation, which reflected respondents’ overall attitudes toward locally grown food.

In order to ensure the quality of the results, independence and normality of the variables were checked. Independence of the variables was examined using residual plots to assess the randomness of the data point spread in the plots. If the residuals were randomly spread on the plots, the variables were independent (Lomax & Hahs-

Vaughn, 2012). Normality of the scores was examined by checking the skewness and kurtosis or running the Shapiro-Wilk test of the variables to ensure the quality of data was proper for further analysis (Lomax & Hahs-Vaughn, 2012). If the values of skewness and kurtosis were both between -2 and 2, or if the result of Shapiro-Wilk test showed no significance, the assumptions of normality were met. The results of the normality checks can be seen in Table 3-3. The assumption of normality was met in all the variables. The index scores generated from this part were used as continuous variables for later correlational and regression analysis.

Correlational Statistics

Correlational analysis was used to accomplish objective four: To determine the relationships between Taiwanese general public’s (a) knowledge, awareness, and past experience of food insecurity issues, (b) attitudes toward Taiwan’s locally grown food,

(c) perceptions of the social pressure to make locally grown food purchases, (d) perceptions of availability, affordability, and accessibility of locally grown food, (e) intention to purchase locally grown food, and (f) demographic characteristics. In order to examine the relationships between the variables, assumptions, including linear

relationships between the variables and independence of the variables, had to be met to use Pearson’s and point biserial correlation coefficients for measurement (Lomax &

Hahs-Vaughn, 2012). To test if the assumptions were met for data analysis, similarly, independence of the continuous variables was analyzed using residual plots to examine the level of randomness of the data points in the plots. Linearity of the dependent variables and independent variables were examined using scatterplots of the dependent variables and the independent variables. If the scatterplots showed a linear trend between the dependent variables and independent variables, the linearity assumption was met.

In the correlational analysis of this study, the inter-correlations were examined between variables of the general public’s (a) knowledge, (b) awareness, and (c) past experience of food insecurity issues, (d) attitudes toward Taiwan’s locally grown food,

(e) perceptions of the social pressure to make locally grown food purchases, (f) perceived behavioral control of purchasing locally grown food, (f) intention to purchase locally grown food, and demographic characteristics of (g) sex, (h) age, (i) city of residence, (j) area of residence, (k) agricultural involvement, (l) having dependent children, and (m) being the decision maker of food purchase in the household.

According to Lomax and Hahs-Vaughn (2012), Pearson’s correlation coefficient was appropriate for use in cases where the independent and dependent variables were both interval. In cases where one variable (either dependent or independent) was interval and the other one was nominal (including dichotomous variables), point biserial coefficients should be used (Lomax & Hahs-Vaughn, 2012).

Multiple Regression Modeling

Multiple regression modeling was used to accomplish objective five, by predicting the general public’s intention to purchase locally grown food using their demographic characteristics, knowledge, awareness, and experience of food insecurity issues, and their attitudes and perceptions of locally grown food. Multiple regression is generally used in education and behavioral sciences to better explain the complexity of human behavior (Lomax & Hahs-Vaughn, 2012). Multiple predictor variables were included in the prediction model to explain the levels of influence each predictor variable had on the criterion variable (Lomax & Hahs-Vaughn, 2012). Prior to analyzing data for modeling, the variables used for analysis should meet the assumptions of multiple linear regression analysis. The assumptions of multiple linear regression analysis include linearity, independence, homoscedasticity, normality of continuous independent variables, normality of errors, fixed values of the independent variables, and noncollinearity of the independent variables. (Keith, 2006; Lomax & Hahs-Vaughn,

2012). The assumptions of linearity, independence, and normality of continuous independent variables were examined similarly to the methods described previously for the descriptive statistics and correlational statistics. Homoscedasticity was examined using the residual plots of each continuous variable. The assumption of homoscedasticity would be met if the spread of the residuals at each value of the independent variables was similar (Keith, 2006). The distribution of the residuals should be examined for its normality in order to meet the assumption of normality of errors

(Keith, 2006). If the histogram of the residuals showed a normal distribution, the assumption of normality of errors was met. Fixed values of the independent variables indicated that the results cannot be used to make predictions using the independent

variables beyond the ranges which were examined in this study. Noncollinearity was tested using the collinearity diagnostics. If the eigenvalues in the collinearity diagnostics were all less than 15, the noncollinearity assumption was met (Lomax & Hahs-Vaughn,

2012). When the data were confirmed to meet all the assumptions, they were further analyzed to establish the prediction model.

According to the conceptual model, a sequential multiple linear regression model was used. The independent variables in the regression model included the Theory of

Planned Behavior variables of (a) attitudes toward locally grown food, (b) subjective norms of purchasing locally grown food, and (c) perceived behavioral control of purchasing locally grown food at the first level; the food insecurity-related variables of

(a) knowledge, (b) past experience, and (c) awareness of food insecurity issues at the second level, and the general public’s demographic characteristics, including sex, age, having dependent children, being the decision-maker of food purchase in the household, agricultural involvement, city of residence, and area of residence, in the third level. The dependent variable of the regression model was the general public’s intention to purchase locally grown food. The significance of each variable was examined to ensure it had sufficient statistical power in the model. The strength of each variable in the model was also examined according to its regression coefficient.

Limitations

A web-based survey with opt-in sampling was used for data collection. Due to the nature of web-based surveys and non-probability sampling methods, limitations can occur in the following areas:

1. Sampling bias – Using a web-based survey limits the possible respondents to those with Internet access (Ary et al., 2010; Dillman et al., 2009). Although the Internet accessibility in Taiwan was 74.5% in 2012 (Tsai, 2014), Internet users

were generally from the younger generation, typically aged 40 and less (Directorate-General of Budget, Accounting and Statistics, Executive Yuan, 2011). Sampling error may occur due to a lack of representation from older groups (Ary et al., 2010).

2. Selection bias – The use of a non-probability opt-in sampling method would cause selection bias because the respondents were not randomly selected for sampling (Baker et al., 2013). Systematic differences may exist between the respondents and non-respondents (Baker et al., 2013). To address this limitation, post hoc adjustment and post-stratification weighting methods were used to strengthen information from the underrepresented groups in the sample (Baker et al., 2013; Kalton & Flores-Cervantes, 2003).

3. Coverage error – Again, using a web-based survey limits the possible respondents to those with Internet access (Ary et al., 2010; Dillman et al., 2009). Therefore, the accessible population led an uncovered proportion (people without Internet access) causing coverage error (Ary et al., 2010; Dillman et al., 2009).

4. Exclusion bias –occurred because of the use of non-probability opt-in sampling method “since the vast majority of the target population [was] likely to have no chance of inclusion in the sample” (Baker et al., 2013, p. 21). Baker et al. (2013) indicated the use of post-stratification weighting methods (Kalton & Flores- Cervantes, 2003) to correct the results in order to overcome exclusion bias. However, assumptions have to be made associated with the efficacy of the adjustment strategy (Baker et al., 2013).

5. Measurement error –occurred if the respondents had problems understanding questions and providing accurate answers, particularly because they were able to ask clarifying questions during the survey completion process (Dillman et al., 2009). This may be a limitation in this study because this study used the instrument created by the researcher rather than a pre-existing instrument. As a result, the validity and reliability of the newly created instrument was examined using expert panel reviews and instrument pilot test.

6. Participation bias –occurred because non-probability sampling methods was used. This affected the representativeness of the results because the characteristics of the survey respondents may tend to be similar. Such a similarity in survey respondents is due to the characteristics of the reached Internet users. This further affected generalizability of this study. In order to reduce the participation bias by ensuring representativeness of the respondents, post-stratification weighting methods were used ex post facto according to the demographic characteristics in the 2015 census data of Taiwan (Baker et al., 2013; Ministry of the Interior, 2015).

7. Nonresponse error – existed in this study because the participation rate was not 100% which indicated the possible differences between the respondents and non-respondents cannot be measured (Dillman et al., 2009). The differences

between the respondents and non-respondents may further impact the generalizability of the results (Dillman et al., 2009).

8. Generalizability – was restricted because of the non-probability sampling method used and cultural and geographical differences in opinions existing in different regions. The results of this study was only applicable to Taiwan and the sampled population.

9. Interpretation issues – The interpretation of the interval variables in this study was influenced by real limits. “Real limits are the boundaries of intervals for scores that are represented on a continuous number line. The real limit separating two adjacent scores is located exactly halfway between the scores” (Gravetter & Wallnau, 2013, p. 22). By averaging the scores, the means may fall between two integers, but be rounded up or down to an integer. Such a process influenced the interpretation which may not fully reflect the true cases.

10. Language related issues – occurred due to the instrument used in this study which was delivered and answered in Taiwan Traditional Chinese. The instrument and results which were translated between English and Taiwan Traditional Chinese caused limitations in reporting due to the language differences. The translated language may not completely reflect the meaning of the results.

11. History effect induced issues – occurred during the data collection process because Taiwan was hit by a powerful typhoon “Dujuan” in late September of 2015 (Mullen, 2015) and food safety related news topics were greatly covered in the media in late September of 2015 (Chou, 2015). These events may have impacted respondents’ decision when responding to the survey. Therefore, the results of this study reflected a snapshot of the general public’s opinions about food insecurity issues and locally grown food under the specific situation at a given point in time.

Summary

This chapter introduced the research design, population and sample, instrumentation, data collection method, and data analysis procedures for this study. In order to understand how the general public’s opinions about food insecurity issues in

Taiwan and locally grown good and their demographic characteristics can affect their intention to purchase locally grown food, a quantitative study was conducted using an online survey research design. The survey instrument was developed by the researcher with the use of existing literature as reference, and reviewed by panels of experts to

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ensure the validity and reliability of the instrument. Prior to being launched in the system, the instrument was reviewed by UFIRB and tested in a pilot study. The survey questionnaires then were delivered to the respondents who were residents living in the

Northern Region of Taiwan aged 18 and older recruited by a public opinion survey company. Once the required number (n = 400) of responses was received, the data were analyzed according to the objectives using descriptive statistics, correlational statistics, and multiple regression modeling.

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Figure 3-1. Map of the Northern Region of Taiwan

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Table 3-1. Reliability coefficients of the index scores of the constructs Reliability Coefficient Index Pilot Test Actual Survey Knowledge .94 .95 Attitude .86 .93 Importance .74 .88 Subjective Norm .91 .91 Perceived Behavioral Control .92 .89 Intention .98 .87

Table 3-2. Weight coefficients of sex, age, and city Demographic Items Weight Coefficient Sex Female .514 Male .486 Age 18-19 .033 20-29 .161 30-39 .208 40-49 .191 50-59 .187 60-69 .127 70-79 .059 80 and older .035 City Taipei City .257 New Taipei City .380 Keelung City .036 Taoyuan City .194 Hsinchu County .049 Hsinchu City .039 Yilan County .044

Table 3-3. Normality of the index scores Variable M SD Skewness Kutosis Knowledge 2.86 1.16 .215 -1.159 Experience 2.55 1.26 .279 -.691 Awareness 6.35 1.34 -.236 .365 Attitude 4.16 0.68 -.382 -.705 Importance 3.90 0.76 -.611 -.033 Subjective Norm 4.09 0.63 -.353 -.092 Perceived Behavioral Control 4.09 0.62 -.416 -.329 Intention 4.47 0.52 -1.108 1.187

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CHAPTER 4 RESULTS

Driven by the Theory of Planned Behavior and the Social Cognitive Theory this study was conducted to explore factors influencing the Taiwanese general public’s support of locally grown food. The objectives of this study were to examine how personal characteristics, cognitive factors, and environmental factors interacted and affected the public’s intention to purchase locally grown food. By using an online survey,

Taiwanese residents living in the Northern Region were sampled to collect their responses.

In this chapter, the results of data analysis were presented. Analysis of descriptive, correlational, and regression statistics were reported in response to the objectives of this study:

Descriptive analysis were conducted

 Obj. 1. To identify Taiwanese general public’s demographics;

 Obj. 2. To identify Taiwanese general public’s levels of knowledge, past experience, and awareness of food insecurity issues; and

 Obj. 3. To identify Taiwanese general public’s (a) attitudes toward Taiwan’s locally grown food and importance of agriculture, (b) perceptions of the social pressure to make locally grown food purchases, (c) perceptions of availability, affordability, and accessibility of locally grown food, and (d) intention to purchase locally grown food.

Correlational analysis were conducted

 Obj. 4. To determine the relationships between Taiwanese general public’s (a) knowledge, past experience, and awareness of food insecurity issues, (b) attitudes toward Taiwan’s locally grown food, (c) perceptions of the social pressure to make locally grown food purchases, (d) perceptions of availability, affordability, and accessibility of locally grown food, (e) intention to purchase locally grown food, and (f) demographic characteristics.

At last, regression analysis was used

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 Obj. 5. To determine if the Taiwanese general public’s (a) knowledge, past experience, and awareness of food insecurity issues, in combination with their (b) demographic characteristics, (c) attitudes toward Taiwan’s locally grown food, (d) perceptions of the social pressure to make locally grown food purchases, (e) perceptions of availability, affordability, and accessibility of locally grown food, and (f) demographic characteristics predicted their intention to purchase locally grown food.

In this chapter, the results were presented in the order of research objectives.

Description of Demographics, Food Insecurity Items, Attitudes toward Locally Grown Food, Subjective Norm, Perceived Behavioral Control, and Intention to Purchase Locally Grown Food

Demographics

Due to a lack of statistics associated with food insecurity issues in Taiwan in the existing literature, demographics of the respondents were recorded in this study in order to describe respondents’ demographic characteristics for future studies as a reference.

The demographic questions in the instrument of this study included sex, age, city of residence, zip code, area of residence, agricultural involvement, education, marital status, number of dependent children, role of food decision-making, occupation, ethnicity, income, and political affiliation. The overall demographics of the original respondents and weighted respondents were shown in Table 4-1.

Original respondents

The respondents were 59% female (n = 246) and 41% male (n = 173). The majority of respondents were in an age range of 20-49 (n = 375, 89%). Taipei City was the city with the most respondents answering the survey (n = 192, 46%), followed by

New Taipei City (n = 125, 30%). Almost half of the respondents were living in downtown areas in a city or town (n = 204, 49%), followed by living in a subdivision of a town or city (n = 113, 27%). About half of the respondents had never been involved in agriculture and no one in their immediate family had ever been involved in agriculture (n

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= 221, 53%), while 29% were not involved in agriculture, but someone in their immediate family was (n = 122). More than half of the respondents had a college degree

(n = 246, 59%), and 17% had a master’s degree (n = 70). The marital status of the respondents were 58% married (n = 244), 40% single (n = 169), and 2% other (n = 6).

When asked the number of dependent children they have, 53% indicated they had no dependent children (n = 223), followed by one dependent children (n = 122, 29%). The majority of the respondents indicated they were the decision-maker when making food purchases (n = 339, 81%), while 19% of them indicated they were not (n = 80). The occupation with the most respondents was business (n = 84, 20%), followed by the service industry (n = 65, 16%) and manufacturing industry (n = 65, 16%). The ethnicity group most respondents indicated was Southern Min (n = 232, 55%), followed by

Mainlander (n = 101, 24%). The income levels with more than half of the respondents was ranged between New Taiwan Dollar (NTD) of $20,000 to NTD$59,999 per month (n

= 236, 56%). Lastly, 59% of the respondents indicated their political affiliation as

“Neither supportive to the ‘Blue’ nor ‘Green’” (n = 247), followed by “Supportive to the

‘Blue’” (n = 80, 19%).

Weighted respondents

By weighting the data using 2015 census statistics of sex, age, and city of residence (Ministry of Interior, 2015), the respondents were comprised of 51% female (n

= 215) and 49% male (n = 204). The age level with the most respondents was 60-69 (n

= 93, 22%), followed by 30-39 (n = 87, 21%). Most respondents lived in New Taipei City

(n = 159, 38%), followed by Taipei City (n = 108, 26%).

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Food Insecurity Items

Perceived knowledge level

Respondents were asked to indicate their perceived knowledge level of seven listed food insecurity issues in Taiwan. The results are shown in Table 4-2. More than half of the respondents indicated they were not at all knowledgeable or slightly knowledgeable about food insecurity issues related to “The proportion of local fresh produce to imported fresh produce in Taiwan” (n = 235, 56%), the “Amount of food needed to feed the people in Taiwan” (n = 222, 53%), and “Taiwan's level of reliance on imported animal feeds” (n = 214, 51%). However, the least responses in not at all knowledgeable or slightly knowledgeable were received in food insecurity issues related to “Reasons for food price fluctuations” (n = 107, 25%) and “Food safety” (n = 110,

26%).

Awareness

Respondents were then asked to answer 10 questions associated with food insecurity issues in Taiwan to measure their awareness of food insecurity issues in

Taiwan. The findings can be seen in Table 4-3. The questions that received more than

90% of correct answers were “The farming land area in Taiwan has decreased due to urbanization” (n = 386, 92%), “An increase in flour consumption, such as breads and noodles, will enhance the reliance on imported food ingredients” (n = 384, 91%), and

“Climate change reduces the quantity of food produced in Taiwan” (n = 378, 90%). The questions with less than 20% of respondents getting the answer correct were “Which of the following groups of food could be produced solely in Taiwan with local farmers able to supply enough to feed the Taiwanese people” (n = 83, 20%) and “Which of the

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following groups of food could not be produced solely in Taiwan with local farmers able to supply enough to feed the Taiwanese people” (n = 73, 17%).

Past experience

Seven options were provided to measure respondents’ past experience with food insecurity issues in Taiwan. The results are shown in Table 4-4. The food insecurity issue that most respondents had experienced was “Food safety issues” (n = 365, 87%), followed by “Increased price of locally grown food” (n = 279, 67%). However, only 2% of the respondents indicated they did not experience any food insecurity issues in the past year (n = 7).

Attitudes

Eight sets of bipolar adjectives were used to measure respondents’ attitudes toward locally grown food in Taiwan. Respondents’ attitudes toward locally grown food were reported in Table 4-5. According to the mean scores of each item in the semantic scale, respondents perceived locally grown food as natural, high quality, fresh, nutritious, tasty, wholesome, safe, and clean. However, the highest score was shown in tasty (M = 4.33, SD = .74), whereas the lowest score was shown in safe (M = 3.96, SD

= .92).

Respondents were asked to indicate their perceived importance of agriculture in

Taiwan using seven statements. Respondents’ perceptions about the importance of agriculture were shown in Table 4-6. Overall, more than half of the respondents indicated agriculture in Taiwan was very important or extremely important in all the asked aspects. The statements received the most very important and extremely important responses was “Agriculture benefits human health” (n = 341, 81%), followed by “Agriculture benefits the society” (n = 332, 79%).

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Subjective Norms

Subjective norms of locally grown food purchases were measured by asking the respondents how they see the important individuals surrounding them would support their purchasing locally grown food. The findings can be seen in Table 4-7. Overall, the respondents agreed or strongly agreed with the statements associated with the support they would receive from important individuals in their lives about their locally grown food purchases. The statements that most respondents agreed or strongly agreed with were

“My family would approve of my purchasing locally grown food” (n = 381, 91%), followed by “My family thinks that I should purchase locally grown food” (n = 336, 80%).

Perceived Behavioral Control

Perceived behavioral control of locally grown food was measured by identifying how respondents perceived the availability, affordability, and accessibility of locally grown food using six statements. The findings were reported in Table 4-8. Generally, the respondents agreed or strongly agreed that locally grown food would be available, affordable, and accessible for them to purchase. The statement receiving the highest in agree or strongly agree responses was “I can afford to purchase locally grown food” (n

= 375, 90%), followed by “I am confident I will always be able to afford locally grown food” (n = 351, 84%).

Intention

Respondents’ intention to purchase locally grown food was measured by eight listed food categories: rice, cereals, vegetables, fruits, eggs, meats, seafood, and milk.

The findings can be seen in Table 4-9. Overall, the majority of the respondents indicated that they are likely or very likely to purchase locally grown food in all the categories in the next 12 months. Within the eight categories of food, more than 90% of

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the respondents indicated they are likely or very likely to purchase locally grown vegetables (n = 398, 95%), fruits (n = 393, 94%), and rice (n = 390, 93%) in the next 12 months.

Relationships between Constructs Associated with Food Insecurity, Locally Grown Food, and Demographical Variables

In order to analyze the relationships between the research constructs, the means of the constructs, including (a) knowledge level of food insecurity issues, (b) attitude towards locally grown food, and (c) subjective norm, (d) perceived behavioral control, and (e) intention of purchasing locally grown food, and the sums of the construct, including (f) awareness and (g) experience of food insecurity issues, were calculated.

The data were weighted in correlational analysis so the findings revealed the situation within the population of interest for the study. The means and standard deviation of each research constructs are presented in Table 4-10. The results of correlation analysis of the research variables were displayed in Table 4-11, Table 4-12, Table 4-13, and Table 4-14. The strength of the relationships between the variables were described using Davis’ (1971) convention with .01 ≥ R ≥ .09 = Negligible, .10 ≥ R ≥ .29 = Low, .30

≥ R ≥ .49 = Moderate, .50 ≥ R ≥ .69 = Substantial, R ≥ .70 = Very Strong.

Food Insecurity Items and Intention

The relationships between the general public’s knowledge, past experience, and awareness of food insecurity issues and their intention to purchase locally grown food were examined using bivariate correlation analysis. The findings were summarized in

Table 4-11. No significant correlations were found between knowledge, past experience, and awareness of food security issues with intention. However, awareness was found to be negatively correlated with knowledge at a low magnitude (r = -.21, p =

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.00), but positively correlated with experience with a moderate magnitude (r = .32, p =

.00).

Attitude, Subjective Norm, Perceived Behavioral Control, and Intention

The findings of the relationships between the general public’s attitudes toward locally grown food, subjective norms and perceived behavioral control of purchasing locally grown food, and intention to purchase locally grown food were shown in Table 4-

11. All the relationships between attitude, subjective norm, perceived behavioral control, and intention were positive. Intention was found to have a low level correlation with attitude (r = .22, p = .00), be moderately correlated with perceived behavioral control (r =

.30, p = .00), and substantially correlated with subjective norm (r = .51, p = .00).

However, a moderate correlation was found between attitude and subjective norm (r =

.47, p = .00), and substantial correlations were found between attitudes and perceived behavioral control (r = .60, p = .00) and subjective norm and perceived behavioral control (r = .60, p = .00).

Demographic Characteristics and Intention

The relationships between demographic characteristics and intention can be seen in Table 4-11 and Table 4-12. Low level positive relationships were found between intention and having dependent children (r = .10, p = .04), being the decision-maker of food purchase in the household (r = .29, p = .01), living in Taoyuan City (r = .23, p = .01), and living in Hsinchu City (r = .12, p = .02); while negative low level magnitudes between intention and living in New Taipei City (r = -.18, p = .00) and living in Hsinchu

County (r = -.12, p = .01) were found.

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Inter-correlations between Research Constructs and Demographic Characteristics

The findings of the inter-correlations between research constructs and demographic characteristics can be seen in Table 4-11, Table 4-12, Table 4-13, and

Table 4-14. Knowledge of food insecurity issues was found to be positively correlated with attitude (r = .38, p = .00) and perceived behavioral control associated with locally grown food (r = .36, p = .00) in moderate magnitudes, while in a low magnitude with subjective norm (r = .29, p = .00). The relationship between awareness of food insecurity issues and the Theory of Planned Behavior variables were all negative. A low level correlation between awareness and subjective norm was found (r = -.11, p = .02), while a moderate correlation with attitude (r = -.31, p = .00) and perceived behavioral control of purchasing locally grown food (r = -.30, p = .00) were found. The relationship between experience of locally grown food and subjective norm of purchasing locally grown food was positive with a low magnitude correlation (r = .17, p = .00).

Significant relationships were also found between demographic variables, food insecurity variables, and the Theory of Planned Behavior variables. Sex was found to have a low level negative correlation with awareness (r = -.23, p = .00) and experience

(r = -.21, p = .00) of food insecurity issues, whereas attitudes toward locally grown food

(r = .14, p = .00) were positive. Age had a negative low level correlation with knowledge of food insecurity issues (r = -.10, p = .04) and attitudes toward locally grown food (r = -

.22, p = .00), but positively correlated with awareness (r = .27, p = .00) and experience

(r = .14, p = .00) of food insecurity issues and subjective norm (r = .14, p = .00) of purchasing locally grown food.

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Having dependent children or not was found to be positively correlated at a low level with knowledge of food insecurity issues (r = .27, p = .00) and attitudes (r = .26, p

= .00), subjective norm (r = .12, p = .01), and perceived behavioral control (r = .22, p =

.00) associated with locally grown food, while negatively correlated with awareness (r =

-.25, p = .00) and experience with food insecurity issues (r = -.12, p = .02). Moderate positive correlations between being the decision-maker regarding food purchase and knowledge of food insecurity issues (r = .33, p = .00), attitudes (r = .32, p = .00), and subjective norm (r = .30, p = .00) were found, while low level correlation with perceived behavioral control (r = .26, p = .00) associated with locally grown food was found.

Agricultural involvement’s relationships with food insecurity variables and the

Theory of Planned Behavior variables also varied by different categories. At the involvement level of “involved in agriculture for a living,” positive correlations were found in knowledge of food insecurity issues (r = .29, p = .00), subjective norm (r = .14, p =

.00), and perceived behavioral control (r = .12, p = .01) associated with locally grown food in low magnitudes, while low and negative correlations were found in awareness (r

= -.15, p = .00) of food insecurity issues. However, significant correlations in low magnitudes of agricultural involvement of “Not personally involved in agriculture, but someone in the immediate family is” were found to be positively correlated with experience of food insecurity issues (r = .18, p = .00), attitude (r = .18, p = .02), and perceived behavioral control (r = .14, p = .01) associated with locally grown food. As for agricultural involvement of “I have never been involved in agriculture and no one in my immediate family has ever been involved in agriculture,” it was found to be negatively correlated with knowledge (r = -.14, p = .00) and experience with food insecurity issues

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(r = -.17, p = .00), attitudes (r = -.25, p = .00), subjective norm (r = -.16, p = .00), and perceived behavioral control (r = -.21, p = .00) associated with locally grown food.

Relationships between city of residence and food insecurity variables and the

Theory of Planned Behavior variables were also examined. Low level relationships were found between living in Taipei City and knowledge of food insecurity issues (r = .15, p =

.00), while negative relationships with experience of food insecurity issues (r = -.16, p =

.00) were found. As for New Taipei City, negative low correlations were found with knowledge of food insecurity issues (r = -.21, p = .00) and attitudes toward locally grown food (r = -.15, p = .00), whereas low and positive correlations were found with awareness (r = .14, p = .01) and experience with food insecurity issues (r = .23, p = .00).

Correlations between living in Taoyuan City were found with awareness (r = -.12, p =

.02) and experience of food insecurity issues (r = -.17, p = .00), while positive correlations with perceived behavioral control of purchasing locally grown food (r = .14, p = .00) in low magnitudes and attitudes toward locally grown food (r = .30, p = .00) in a moderate magnitude were found. A significant correlation was found between living in

Hsinchu County and awareness of food insecurity issues (r = .11, p = .03). In contrary, a correlation between living in Hsinchu City and awareness of food insecurity issues was found in a negative fashion with a low magnitude (r = -.10, p = .05). While living in Yilan

County was found to be significantly correlated with experience of food insecurity issues

(r = .16, p = .00), attitudes (r = -.17, p = .00) and subjective norms associated with locally grown food (r = -.10, p = .04).

Lastly, the relationships between area of residence and food insecurity variables and the Theory of Planned Behavior variables varied by categories. Living in a rural

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area not a farm was found to have a low level correlation with knowledge of food insecurity issues (r = .20, p = .00) and perceived behavioral control of purchasing locally grown food (r = .10, p = .04), while being negatively correlated with experience with food insecurity issues (r = -.13, p = .01). As for living in urban or suburban area outside of city limits, low level negative correlations were found with knowledge of food insecurity issues (r = -.24, p = .00), attitudes (r = -.21, p = .00), subjective norm (r = -.11, p = .03), and perceived behavioral control (r = -.27, p = .00) associated with locally grown food.

Negative correlations with low magnitudes were also found between living in a subdivision in a town or city and knowledge of food insecurity issues (r = -.15, p = .00) and attitudes towards locally grown food (r = -.12, p = .01). The low correlations between living in a downtown area in a city or town and knowledge (r = .25, p = .00) and experience with food insecurity issues (r = .12, p = .02), attitudes (r = .25, p = .00), subjective norm (r = .12, p = .01), and perceived behavioral control (r = .26, p = .00) associated with locally grown food were found to be positive, whereas it was negatively correlated with awareness of food insecurity issues (r = -.11, p = .03).

Predicting Purchase of Locally Grown Food Using Demographics, Food Insecurity Items, Attitudes, Subjective Norm, and Perceived Behavioral Control

Based on the conceptual model, a prediction model of the public’s intention to purchase locally grown food (dependent variable) was developed using the independent variables of (a) demographics, (b) knowledge, past experience, and awareness of food insecurity issues, (c) attitudes toward locally grown food, (d) perceived importance of agriculture, (e) subjective norms of purchasing locally grown food, and (f) perceived behavioral control of purchasing locally grown food. The demographic characteristics used in the model were sex, age, having dependent children, being the decision-maker

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of food purchase in the household, agricultural involvement, city of residence, and area of residence. The categorical demographic variables were dummy coded into new dummy variables in the model. Note that the weighted data were used in regression analysis, therefore, the results illustrated the situation in the population of interest.

According to Lomax and Hahs-Vaughn (2012) and Keith (2006), seven assumptions of multiple linear regression were examined: linearity, independence, homoscedasticity, normality of continuous independent variables, normality of errors, fixed values of the independent variables, and noncollinearity of the independent variables. As all the assumption were met, the result of sequential multiple regression can be seen in Table 4-15.

The sequential multiple linear regression model was developed using three levels. The first level only included the Theory of Planned Behavior variables of (a) attitudes toward locally grown food, (b) subjective norms of purchasing locally grown food, and (c) perceived behavioral control of purchasing locally grown food. The second level incorporated food insecurity-related variables into the model: (a) knowledge, (b) past experience, and (c) awareness of food insecurity issues. Lastly, selected demographic variables were added into the third level of the regression model, including sex, age, having dependent children, being the decision-maker of food purchase in the household, agricultural involvement, city of residence, and area of residence. All three models were found to be statistically significant with R2 of .264 (F(3, 415) = 49.644, p =

.000), .308 (F(6, 412) = 30.585, p = .000), and .443 (F(24, 394) = 13.067, p = .000), respectively. The R2 changes were also tested to examine the best-fit model to predict intention to purchase locally grown food using the Theory of Planned Behavior

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variables, food insecurity variables, and demographic variables. By adding new sets of variables to the model, more variation in intention of purchasing locally grown food was explained by the added variables. The addition of food insecurity variables to the prediction model increased the R2 by .04 (F(3, 411) = 8.746, p = .000). Moreover, the addition of another set of the demographic variables to the model led to a .14 increase of the R2 (F(18, 393) = 5.309, p = .000). Therefore, Model 3, including the Theory of

Planned Behavior variables, the food insecurity related variables, and the selected demographic variables, was considered as the best-fit model to predict intention to purchase locally grown food.

Each independent variable’s impact on the dependent variable, intention of purchasing locally grow food, in the model was reported in Table 4-16. In Model 1, when only the Theory of Planned Behavior variables were used to predict intention, subjective norm (b = .451, t(415) = 9.881, p = .000) was the only significant predictor of intention.

When the food insecurity variables were added into the model (Model 2), the significant predictors of intention were subjective norm (b = .473, t(412) = 10.404, p = .000), awareness (b = .060, t(412) = 3.442, p = .001), and experience (b = -.070, t(412) = -

3.957, p = .000). When the Theory of Planned Behavior variables, food insecurity variables, and demographic variables were included, the significant predictors of intention were (a) subjective norm (b = .442, t(394) = 9.829, p = .000), (b) perceived behavioral control (b = .099, t(394) = 2.199, p = .028), (c) knowledge (b = -.058, t(394) =

-2.320, p = .021), (d) awareness (b = .069, t(394) = 4.098, p = .000), (e) being the food decision-maker (b = .234, t(394) = 4.167, p = .000), agricultural involvement levels of (f) involved in agriculture for a living (b = -.261, t(394) = -2.290, p = .023) and (g) not

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involved in agriculture, but someone in my immediate family is, (b = -.161, t(394) = -

3.366, p = .001) when compared to someone with agricultural involvement of never been involved in agriculture and no one in my immediate family has ever been involved in agriculture, city of residence of (h) New Taipei City (b = -.130, t(394) = -2.269, p =

.024), (i) Taoyuan City (b = .146, t(394) = 2.152, p = .032), (j) Hsinchu County (b = -

.306, t(389) = -2.806, p = .005), and (k) Hsinchu City (b = .291, t(394) = 2.570, p = .011) when compared to someone living in Taipei City, and area of residence of (l) living in urban or suburban area outside of city limits (b = .166, t(394) = 2.855, p = .005) when compared to someone living in downtown area in a city or town.

Summary

The findings of this study were presented in this chapter. Respondents’ (a) demographics, (b) knowledge, past experience, and awareness of food insecurity issues, (c) attitudes toward locally grown food, (d) perceived importance of agriculture,

(e) subjective norms of purchasing locally grown food, (f) perceived behavioral control of purchasing locally grown food, and (g) intention to purchase of locally grown food were evaluated and described using descriptive statistics in order to accomplish Objectives 1,

2, and 3. The descriptive statistics provided an overview about who the respondents were and revealed the respondents’ opinions about how they feel and think about agriculture, locally grown food, and food insecurity issues in Taiwan.

Correlational analysis was used to examine Objective 4 about the relationships between the dependent and independent variables. Significant relationships were found between food insecurity variables, Theory of Planned Behavior variables, and demographic variables. Lastly, sequential multiple linear regression was used to reach

Objective 5 to predict the public’s intention to purchase of locally grown food by their (a)

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demographic characteristics of sex, age, having dependent children or not, being the decision maker regarding food purchase, agricultural involvement, city of residence, and area of residence, (b) knowledge, past experience, and awareness of food insecurity issues, (c) attitudes toward locally grown food, (d) subjective norms of purchasing locally grown food, and (e) perceived behavioral control of purchasing locally grown food. The regression models were found statistically significant. The regression analysis showed that individuals’ intention to purchase locally grown food can be best predicted by their (a) subjective norm, (b) perceived behavioral control, (c) knowledge, (d) awareness, (e) being the food decision-maker, (f) agricultural involvement levels of involved in agriculture for a living and (g) not involved in agriculture, but someone in my immediate family is, when compared to someone with agricultural involvement of never been involved in agriculture and no one in my immediate family has ever been involved in agriculture, (h) city of residence of New Taipei City, (i) Taoyuan City, (j) Hsinchu

County, and (k) Hsinchu City when compared to someone living in Taipei City, and (l) area of residence of living in an urban or suburban area outside of city limits when compared to someone living in a downtown area in a city or town. These significant predictors accounted for 44% of variation in the intention to purchase locally grown food.

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Table 4-1. Demographics of the respondents Original Weighted* Demographic Items n % n % Sex Female 246 58.7 215 51.4 Male 173 41.3 204 48.6 Age 18-19 5 1.2 14 3.3 20-29 93 22.2 67 16.1 30-39 158 37.7 87 20.8 40-49 124 29.6 80 19.1 50-59 31 7.4 78 18.7 60-69 8 1.9 93 22.1 70 and older 0 0 0 0 City of Residence Taipei City 192 45.8 108 25.7 New Taipei City 125 29.8 159 38.0 Keelung City 18 4.3 15 3.6 Taoyuan City 54 12.9 81 19.4 Hsinchu County 8 1.9 21 4.9 Hsinchu City 13 3.1 16 3.9 Yilan County 9 2.1 18 4.4 Area of Residence A farm in rural area 9 2.1 Rural area, not a farm 29 6.9 Urban or suburban area outside of city limits 64 15.3 Subdivision in a town or city 113 27.0 Downtown area in a city or town 204 48.7 Agricultural Involvement I am involved in agriculture for a living 45 10.7 I am involved in agriculture as a hobby 28 6.7 I have been involved in agriculture in the past 3 0.7 I am not involved in agriculture, but someone 122 29.1 in my immediate family is I have never been involved in agriculture and 221 52.7 no one in my immediate family has ever been involved in agriculture Education Did not graduate high school 5 1.2 High school graduate 24 5.7 Professional school graduate 36 8.6 Some college, no degree 29 6.9 College degree 246 58.7 Master's degree 70 16.7 Doctoral degree 9 2.1 Note. *Data were only weighted by sex, age, and city of residence.

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Table 4-1. Continued Original Weighted* Demographic Items n % n % Marital Status Single 169 40.3 Married 244 58.2 Other 6 1.4 Dependent Children 0 223 53.2 1 122 29.1 2 64 15.3 3 7 1.7 4 1 0.2 Food Decision-maker Yes 339 80.9 No 80 19.1 Occupation Industrial industry 27 6.4 Business 84 20.0 Service industry 65 15.5 Student 27 6.4 Manufacturing industry 65 15.5 Military, police, governmental officer 15 3.6 Education, research 58 13.8 Agricultural industry 7 1.7 Self-employed profession 25 6.0 Housewife/househusband 20 4.8 Retired 5 1.2 Unemployed 15 3.6 Other 6 1.4 Ethnicity Groups Taiwan•born Taiwanese • Southern Min 232 55.4 Taiwan•born Taiwanese • Hakka 60 14.3 Taiwan•born Taiwanese • Mainlander 101 24.1 Taiwan•born Taiwanese • Native 37 8.8 Taiwanese Foreign•born Taiwanese 7 1.7 Foreigner 7 1.7 Other 4 1.0 Income Less than $20,000 73 17.4 $20,000 • $39,999 106 25.3 $40,000 • $59,999 130 31.0 $60,000 • $79,999 63 15.0 $80,000 and more 47 11.2 Note. *Data were only weighted by sex, age, and city of residence.

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Table 4-1. Continued Original Weighted* Demographic Items n % n % Political Affiliation Very supportive to the "Blue" 22 5.3 Supportive to the "Blue" 80 19.1 Neither supportive to the "Blue" nor 247 58.9 "Green" Supportive to the "Green" 56 13.4 Very supportive to the "Green" 14 3.3 Note. *Data were only weighted by sex, age, and city of residence.

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Table 4-2. Knowledge level of food insecurity issues in Taiwan Level of Knowledge (%) Items NK SL SW KL VK The proportion of local fresh 36.3 19.8 17.4 16.0 10.5 produce to imported fresh produce in Taiwan Amount of food needed to feed the 27.2 25.8 17.7 16.5 12.9 people in Taiwan Taiwan's level of reliance on 32.7 18.4 15.5 18.9 14.6 imported animal feeds Amount of food produced in 22.7 24.8 19.8 18.1 14.6 Taiwan Taiwan's level of reliance on 21.5 17.7 18.4 28.4 14.1 imported fuel Food safety 6.0 19.8 31.0 27.2 16.0 Reasons for food price fluctuations 5.7 19.8 31.0 28.4 15.0 Note. Scale: NK = Not at All Knowledgeable, SL = Slightly Knowledgeable, SW = Somewhat Knowledgeable, KL = Knowledgeable, VK = Very Knowledgeable.

Table 4-3. Awareness of food insecurity issues in Taiwan Items % of Correct The farming land area in Taiwan has decreased due to urbanization. 92.1 An increase in flour consumption, such as breads and noodles, will 91.6 enhance the reliance on imported food ingredients. Climate change reduces the quantity of food produced in Taiwan. 90.2 When consumers lose trust due to food safety issues, it can lead to 89.3 national food insecurity. The small farm production system in Taiwan has led to increased 80.0 competition of locally produced food with imported food in the market. Climate change reduces the quality of food produced in Taiwan. 70.9 The small farm production system in Taiwan has decreased the 57.5 production costs for growers. The majority of the food consumed in Taiwan is locally produced. 27.2 Which of the following groups of food could be produced solely in 19.8 Taiwan with local farmers that able to supply enough to feed the Taiwanese people? Which of the following groups of food could not be produced solely in 17.4 Taiwan with local farmers that able to supply enough to feed the Taiwanese people?

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Table 4-4. Experience of food insecurity issues in Taiwan Items n % Food safety issues (e.g., tainted products, pathogen 365 87.1 contaminated fresh produce) Increased price of locally grown food 279 66.6 Shortage of any given type of fresh produce/ingredient used for 201 48.0 daily consumption The price of fresh produce (imported or local) became 172 41.1 unaffordable without warning Loss of access to any given type of locally grown food 48 11.5 None of above 7 1.7 Other 4 1.0

Table 4-5. Attitudes toward Taiwan’s locally grown food Item M SD Tasty : Not Tastya 4.33 .74 Fresh : Not Fresha 4.30 .78 High Quality : Low Quality 4.25 .76 Natural : Unnatural 4.20 .85 Nutritious : Not Nutritious 4.18 .84 Wholesome : Not Wholesome 4.06 .87 Clean : Dirty 4.03 .84 Safe : Unsafea 3.96 .92 Note. Responses based on semantic differential scale. Note. aReverse-coded items.

Table 4-6. Perceived importance of agriculture in Taiwan Level of Importance (%) Items NI SI I VI EI Agriculture benefits human health 0.5 4.3 13.8 34.4 47.0 Agriculture benefits the society 0.5 4.5 15.8 31.0 48.2 Agriculture benefits the economy 0.0 7.6 21.2 32.0 39.1 Agriculture benefits wildlife habitats 1.4 6.9 22.0 32.9 36.8 Agriculture benefits the natural 1.7 13.8 18.1 34.4 32.0 beauty of the landscape Agriculture benefits national 3.8 14.1 23.2 30.3 28.6 security Agriculture benefits job 1.9 16.9 31.3 34.1 15.8 opportunities Note. Scale: NI = Not at All Important, SI = Slightly Important, I = Important, VI = Very Important, EI = Extremely Important.

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Table 4-7. Subjective norms of purchasing locally grown food Level of Agreement/Disagreement (%) Items SD D NDNA A SA My family would approve of my 0.0 0.0 9.1 45.1 45.8 purchasing locally grown food My family thinks that I should 0.2 0.2 19.3 43.4 36.8 purchase locally grown food My best friend(s) would approve 0.2 0.7 20.3 50.1 28.6 of my purchasing locally grown food My best friend(s) thinks that I 0.2 1.0 23.9 44.6 30.3 should purchase locally grown food My colleagues would approve of 0.2 1.4 27.9 42.5 27.9 my purchasing locally grown food My colleagues thinks that I should 0.2 1.2 28.9 42.2 27.4 purchase locally grown food Note. Scale: SD = Strongly Disagree, D = Disagree, NDNA = Neither Disagree nor Agree, A = Agree, SA = Strongly Agree.

Table 4-8. Perceived behavioral control of purchasing locally grown food Level of Agreement/Disagreement (%) Items SD D NDNA A SA I can afford to purchase locally 0.0 0.5 10.0 53.5 36.0 grown food I am confident I will always be 0.2 1.7 14.3 47.5 36.3 able to afford locally grown food I am able to locate sufficient 0.0 3.6 16.0 49.9 30.5 amounts of locally grown food I am confident locally grown food 0.0 5.0 17.4 49.6 27.9 is available whenever I want I have access to locally grown 0.2 3.6 19.6 48.4 28.2 food I am confident I will always have 0.2 2.9 20.5 48.7 27.7 access to locally grown food Note. Scale: SD = Strongly Disagree, D = Disagree, NDNA = Neither Disagree nor Agree, A = Agree, SA = Strongly Agree.

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Table 4-9. Intention to purchase locally grown food Level of Likelihood (%) Items VU U NLNU L VL I intend to purchase locally grown 0.2 0.5 4.3 30.1 64.9 vegetables I intend to purchase locally grown 0.0 0.7 5.5 32.7 61.1 fruits I intend to purchase locally grown 0.2 0.0 6.4 25.8 67.3 rice I intend to purchase locally grown 1.4 0.2 8.4 38.9 51.1 meats I intend to purchase locally grown 0.2 1.2 9.1 28.6 60.9 eggs I intend to purchase locally 1.4 0.7 8.6 36.0 53.2 grown/caught seafood I intend to purchase locally 0.7 0.7 9.5 30.1 58.9 produced milk I intend to purchase locally grown 0.7 1.9 11.0 34.8 51.6 cereal (grains other than rice) Note. Scale: VU = Very Unlikely, U = Unlikely, NLNU = Neither Likely nor Unlikely, L = Likely, VL = Very Likely.

Table 4-10. Means and standard deviations of the research constructs Construct M SD Awareness of Food Insecurity Issuesa 6.78 1.39 Intention to Purchase Locally Grown Foodb 4.48 0.52 Subjective Norms of Purchasing Locally Grown Foodb 4.05 0.61 Attitude towards Locally Grown Foodb 3.95 0.73 Perceived Behavioral Control of Purchasing Locally Grown Foodb 3.93 0.66 Experience of Food Insecurity Issuesc 2.81 1.31 Knowledge Level of Food Insecurity Issuesb 2.60 1.00 Note. aIndex score calculated by summing up the items ranging from zero to 10. bIndex score calculated by averaging over the items ranging from one to five. cIndex score calculated by summing up the items ranging from zero to five.

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Table 4-11. Inter-correlations between the research constructs and demographics of sex, age, and income Variable 1 2 3 4 5 6 7 8 9 10 11 1. Knowledge 1.00 2. Awareness -.21** 1.00 3. Experience -.08 .32** 1.00 4. Attitude .38** -.31** -.06 1.00 5. Subjective .29** -.11* .17** .47** 1.00 Norms 6. Perceived .36** -.30** .06 .60** .60** 1.00 Behavioral Control 7. Intention .05 .05 -.04 .22** .51** .30** 1.00 8. Sex .00 -.23** -.21** .19** .00 .00 .08 1.00 9. Age -.10* .27** .14** -.22** .14** -.03 .07 -.48** 1.00 10. Children .27** -.25** -.12* .26** .12* .22** .10* .15** -.14** 1.00 11. Decision- .33** -.04 -.04 .32** .30** .26** .29** .12* .07 -.11* 1.00 maker Note. *Correlation is significant at the .05 level. Note. **Correlation is significant at the .01 level

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Table 4-12. Inter-correlations between the research constructs and demographics Variable 1 2 3 4 5 6 7 8 9 10 11 12. Ag. Inv.-living .29** -.15** -.09 .09 .14** .12* -.03 .14** -.12* .18** .11* 13. Ag. Inv.-hobby .07 .04 .07 .07 .09 .07 .00 -.11* -.01 .04 .12* 14. Ag. Inv.- past .03 -.03 -.04 .07 .07 -.05 .04 .03 -.02 .07 .03 15. Ag. Inv.-No -.01 .02 .18** .18** .05 .14** -.06 .01 -.12* -.14** .11* personal inv., but family inv. 16. Ag. Inv.- No -.14** .02 -.17** -.25** -.16** -.21** .06 -.02 .17** .03 -.21** personal inv., no family inv. 17. Taipei City .15** -.05 -.16** -.08 .01 -.03 .04 .03 .34** -.02 .12* 18. New Taipei -.21** .14** .23** -.15** -.03 -.03 -.18** -.13** .09 -.17** -.21** City 19. Keelung City .04 -.04 -.09 .01 -.02 -.03 -.03 .10* -.16** .08 -.06 20. Taoyuan City .07 -.12* -.17** .30** .09 .14** .23** .05 -.17** .17** .13** 21. Hsinchu -.06 .11* .04 .03 -.02 -.04 -.12* .03 -.10* -.05 .07 County 22. Hsinchu City .01 -.10* -.00 .08 .00 .02 .12* .06 -.13** .05 .07 23. Yilan County .05 .02 .16** -.17** -.10* -.09 -.06 -.05 -.25** .04 -.09 24. Rural- Farm .05 -.02 -.03 .03 .08 .02 -.01 .04 -.07 -.05 .02 25. Rural- Not .20** -.09 -.13* .09 .07 .10* .01 -.02 -.05 .08 .09 farm 26. Urban- -.24** .07 -.07 -.21** -.11* -.27** .06 .00 .09 -.12* -.25** Outside City 27. Urban- -.15** .10 -.00 -.12* -.09 -.09 -.01 .03 -.12* -.12* .01 Subdivision 28. Urban- .25** -.11* .12* .25** .12* .26** -.04 -.03 .07 .19** .17** Downtown Note. *Correlation is significant at the .05 level. Note. **Correlation is significant at the .01 level

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Table 4-13. Inter-correlations between the research constructs and demographics Variable 12 13 14 15 16 17 18 19 20 21 22 23 12. Ag. Inv.-living 1.00 13. Ag. Inv.-hobby -.05 1.00 14. Ag. Inv.- past -.01 -.01 1.00 15. Ag. Inv.-No -.15** -.19** -.04 1.00 personal inv., but family inv. 16. Ag. Inv.- No -.23** -.28** -.06 -.80** 1.00 personal inv., no family inv. 17. Taipei City .12* -.08 .00 -.16** .15** 1.00 18. New Taipei -.05 -.01 -.04 .01 .02 -.46** 1.00 City 19. Keelung City .05 .00 .21** -.06 .02 -.11* -.15** 1.00 20. Taoyuan City -.03 -.08 -.03 .11* -.05 -.29** -.39** -.10 1.00 21. Hsinchu -.05 .28** -.01 .05 -.16** -.13** -.18** -.04 -.11* 1.00 County 22. Hsinchu City -.04 .02 -.01 .07 -.06 -.12* -.16** -.04 -.10* -.05 1.00 23. Yilan County -.04 .03 -.01 .06 -.05 -.13** -.17** -.04 -.11 -.05 -.04 1.00 24. Rural- Farm .19** -.03 -.01 .09 -.15** -.02 -.07 -.03 .01 .14** -.03 .08 25. Rural- Not .27** .07 -.01 -.12* -.02 .02 -.10* -.04 .13** -.05 -.04 .06 farm 26. Urban- -.11* -.03 -.03 -.04 .10* -.03 .04 .01 .08 -.07 -.03 -.08 Outside City 27. Urban- -.09 -.04 -.04 .18** -.11* .03 -.05 .02 -.04 .03 .01 .06 Subdivision 28. Urban- .02 .04 .06 -.11* .07 -.01 .07 -.00 -.08 .01 .04 -.03 Downtown Note. *Correlation is significant at the .05 level. Note. **Correlation is significant at the .01 level

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Table 4-14. Inter-correlations between specific demographics Variable 24 25 26 27 28 24. Rural- Farm 1.00 25. Rural- Not farm -.03 1.00 26. Urban- Outside -.07 -.11* 1.00 City 27. Urban- -.09 -.13** -.34** 1.00 Subdivision 28. Urban- -.12* -.18** -.47** -.56** 1.00 Downtown Note. *Correlation is significant at the .05 level. Note. **Correlation is significant at the .01 level

Table 4-15. Sequential multiple linear regression model predicting intention to purchase locally grown food Model R2 R2 Change Significance of R2 Change Model 1 .264** Model 2 .308** .044 .000** Model 3 .443** .135 .000** Note. **p < .01.

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Table 4-16. Regression coefficients of the sequential multiple linear regression model predicting intention to purchase locally grown food Variables Model 1 Model 2 Model 3 Theory of Planned Behavior Variables Attitude -.019 -.004 -.053 Subjective Norms .451** .473** .442** Perceived Behavioral Control -.003 .042 .099* Food Insecurity Variables Knowledge -.039 -.058* Experience -.070** -.032 Awareness .060** .069** Demographic Variables Female .050 Age -.002 Dependent Children .036 Food Decision-maker .234** Ag. Involve- for a livinga -.261* Ag. Involve- as a hobbya -.103 Ag. Involve- in the pasta .153 Ag. Involve- No personal involve., -.161** but family involve.a New Taipei Cityb -.130* Keelung Cityb -.097 Taoyuan Cityb .146* Hsinchu Countyb -.306** Hsinchu Cityb .291* Yilan Countyb .045 Rural- Farmc -.016 Rural- Not farmc -.049 Urban- Outside Cityc .166** Urban- Subdivisionc .067 Note. *p < .05; **p < .01. a Comparison group: I have never been involved in agriculture and no one in my immediate family has ever been involved in agriculture. b Comparison group: Taipei City. c Comparison group: Downtown area in a city or town.

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CHAPTER 5 CONCLUSIONS, IMPLICATIONS, AND RECOMMENDATIONS

Conclusions

The findings of this study provided information about the current public perceived knowledge, awareness, and experience with food insecurity issues in Taiwan and public beliefs (attitudes, subjective norms, perceived behavioral control) about locally grown food. Additionally, it provided insight into how the general public’s purchasing behaviors of locally grown food were influenced by their personal background, attitudes, subjective norms, and perceived behavioral control associated with locally grown food, and knowledge, experience, and awareness of food insecurity issues.

Demographics

This study revealed the demographic characteristics online survey respondents may have in the Northern Region of Taiwan. The respondents sampled from the residents living in the Northern Region aged 18 and older in this study tended to be female, an age range between 20 and 49, located in Taipei City or New Taipei City, living in a downtown area in a city or town or a subdivision in a town or city, without personal agricultural involvement, with a college degree, married, without dependent children, involved in business, the service industry, the manufacturing industry, or education/research, perceiving their ethnicity identity as Southern Min or Mainlander, with a personal monthly income level between $20,000 and $59,999 in New Taiwan

Dollar, and reporting their political affiliation as “Neither supportive to the ‘Blue’ nor

‘Green’.”

The National Development Council (2015) discussed the Internet usage in

Taiwan by gender, age, and cities and indicated that: a) male Internet users tended to

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be more active than female users; b) the Internet use rate was highest in people aged

40 and younger, followed by age of 40-49, but low in age of 60 and older; and c) the

Internet usage in the Northern Region was highest in Taipei City and Hsinchu City. The finding in sex was opposite to the finding of the National Development Council’s (2015) study with more female respondents recruited in this study. As for age, the finding in this study was similar to the National Development Council’s (2015) study that the major

Internet users were aged 49 and younger. Note that in this study, no respondent aged

70 and older was recruited. To discuss the respondents by city of residence, the population by cities should also be considered. According to the 2015 census data from the Department of Household Registration, Minister of Interior (2015), the population in the Northern Region was highest in New Taipei City, followed by Taipei City, and lowest in Keelung City. However, the respondents recruited in this study distributed differently from the census statistics. Therefore, the weighted data were reflective to the population, whereas a lack of sampled respondents aged 70 and older made the sector unable to be weighted and limit the generalizability to the population. The weighted data can only reflect the residents living in the Northern Region of Taiwan aged between 18 and 70.

Food Insecurity Issues

Knowledge

When talking about food insecurity issues, most respondents indicated they had limited knowledge of (not at all knowledgeable or slightly knowledgeable) particular topics related to specific agricultural statistics, including a) the proportion of local fresh produce to imported fresh produce in Taiwan, b) amount of food needed to feed the people in Taiwan, c) Taiwan's level of reliance on imported animal feeds, and d) amount of food produced in Taiwan. However, the item of “Taiwan's level of reliance on

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imported fuel” was not directly related to agriculture compared to the other items, while relatively more respondents perceived they knew this topic better. Significant shifts in perceived knowledge level increase were found in food safety and reasons for food price fluctuations. Such a result may be due to recent media coverage about food safety issues and the food price increase caused by severe weather during the data collection process. Even though research statistics about the knowledge level of food insecurity issues were not available in the existing literature, the findings were supportive of the statement that the Taiwanese general public has had low levels of knowledge about food insecurity (Ministry of Foreign Affairs, 2013; Peng, 2011; Tsai, 2011).

Awareness

The awareness scores of food insecurity issues showed that the respondents had a fair level of awareness of food insecurity issues in Taiwan. Based on the arrangement of the fact questions associated with food insecurity, on average, the respondents were able to answer almost seven questions correctly out of the 10 questions. Such a finding indicated that the general public’s awareness of food insecurity issues may be higher than expected (Ministry of Foreign Affairs, 2013; Peng,

2011; Tsai, 2011). However, the approach used to measure awareness in this study identified the actual knowledge level of the respondents as a proxy for awareness.

Therefore, the finding should be interpreted as that the respondents had a fair level of actual knowledge of food insecurity issues in Taiwan.

While exploring the results by question items, less respondents answered the more specific questions about agriculture correctly. More respondents were able to provide correct answers when questions were asked about larger scale questions (e.g., farm land decrease, food consumption, and climate impact to agriculture), while fewer

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correct answers were received when questions were asked about the small farm production system and food production, and even fewer when asked about the production of specific food categories.

Experience

The findings related to experience with food insecurity issues indicated almost all the respondents had experienced at least one of the listed food insecurity issues.

Almost 90% of the respondents indicated they had experienced food safety issues, which was supported by the study conducted by Wei et al. (2010) that the general public has been impacted by news coverage. The high responses in “Increased price of locally grown food” may reflect the adverse impact by the Dujuan typhoon (Mullen, 2015) on food price. Relatively low responses in “Shortage of any given type of fresh produce/ingredient used for daily consumption,” “The price of fresh produce (imported or local) became unaffordable without warning,” and “Loss of access to any given type of locally grown food” showed that the general public in the Northern Region of Taiwan were less likely to perceive the availability, affordability, and accessibility of locally grown food as an issue. Such a finding revealed a similarity to Cheng’s (2010) study since the residents of the Northern Region were characterized as having higher income and educational levels, having a non-farmer job, and having no dependent children.

Therefore, the residents of the Northern Region were less likely to be the undernourished population.

Attitudes toward Locally Grown Food and Perceived Importance of Agriculture

The findings of this study indicated that the respondents generally had positive attitudes toward locally grown food and perceived agriculture as important in various aspects. The positive attitudes revealed in this study were similar to the findings of

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Huang’s (2014) study that consumers had positive attitudes toward local food. In addition, similarity with studies conducted by Chang (2012) and Ou et al. (2011) was also found in that the respondents thought locally grown food in Taiwan was tasty, in high quality, and safe. However, in contrary, the respondents’ positive attitude toward the high quality of locally grown food was opposite to Lai’s (2006) finding that

Taiwanese consumers thought the quality of locally grown food was inconsistent.

In this study, the findings revealed the respondents’ perception of the importance of agriculture in Taiwan. More respondents perceived that agriculture was important in providing benefits to human health, society, economy, ecology, and the environment.

Similar to Chang’s (2013) and Chiou’s (2003) studies, the respondents perceived that agriculture was important to provide benefits to the society. The respondents’ high responses in the benefits of agriculture contributing to human health and wildlife habitats somewhat aligned with the findings found in various organic agriculture-related studies (Hsu, 2011; Lin, 1998; Lin & Ting, 1999; Wang, 2013; Yu, 1998). However, fewer respondents perceived that agriculture could benefit job opportunities (50%).

Interestingly, the responses showed that a majority of the respondents agreed with the benefits agriculture has brought to the economy, whereas less of them perceived agriculture could provide good job opportunities.

Subjective Norm of Purchasing Locally Grown Food

While the majority of the respondents indicated that their purchase of locally grown food was supported and influenced by important individuals in their lives, the findings showed that their family was the most supportive and influential persons to the respondents’ purchases of locally grown food, followed by their best friend(s) and colleagues. Such findings confirmed Lien and Chen’s (2010) and Chang’s (2011)

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studies that Taiwanese consumers may take their families, friends, and colleagues’ opinions in to consideration when making environmentally friendly food purchases.

Similarities were found when comparing the findings in this study to Wu and Chen’s

(2014) study. Both studies revealed family and friends’ influences on individuals’ behavioral intention related to green food purchases and family’s approval of green consumption was more influential than their friends’ approval (Wu & Chen, 2014).

Perceived Behavioral Control of Purchasing Locally Grown Food

Perceived behavioral control in this study was indicated by perceived availability, affordability, and accessibility of locally grown food. The findings indicated that a majority of the respondents perceived that locally grown food was available, affordable, and accessible to them. However, a relatively less amount of respondents perceived locally grown food as accessible compared to available and affordable. Such a finding supported Peng’s (2011) opinion and aligned with Cheng’s (2010) finding that most people perceived they can afford to make food purchases. However, the availability of locally grown food should be low according to the information provided by COAEY

(2014a), while most of the respondents perceived the availability of locally grown food as sufficient. Moreover, while access to locally grown food has been available to the general public (Chuang, 2008; Hsu, 2000; Lee, 2006; Wan et al., 2010), relatively less respondents perceived the accessibility of locally grown food was secure.

Intention to Purchase Locally Grown Food

More than 85% of the respondents indicated they were likely to purchase locally grown food regardless of the types in the next 12 months. Such a finding was similar to the findings of Wan et al. (2010) about locally grown food purchases. Within the eight listed food categories, the lowest intention to purchase was found in cereals followed by

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milk. This finding aligned with the data provided by COAEY (2014a) that cereals and milk had the lowest local production volume in Taiwan. However, a relatively low intention to purchase was found in seafood, which can be completely locally produced or caught in Taiwan (COAEY, 2014a). As for meats, the availability of locally grown meats varied by types. Beef had a low availability and poultry had a high availability

(COAEY, 2014a; Liu et al., 2013). The respondents’ intention to purchase locally grown meats were relatively high, whereas it may not be fully available in the market.

Key Relationships between Variables

While the Ministry of Foreign Affairs (2013), Peng (2011), and Tsai (2011) indicated that the Taiwanese general public had low levels of food insecurity knowledge and awareness, this study showed that when the respondents’ perceived knowledge level of food insecurity issues increased, their awareness of food insecurity issues significantly decreased. Based on the measurement approaches for knowledge and awareness used in this study, the awareness scores can also be interpreted as actual knowledge since the awareness questions had true correct answers. Therefore, such a finding revealed the gap between the respondents’ perceived knowledge level and actual knowledge level. The relationship found between awareness and experience indicated that the higher the respondents’ awareness score was, the more food insecurity issues they tended to experience. This finding indicated that cognition and understanding of the food insecurity issues may enhance a respondent’s attention to feel or see what is happening with food insecurity issues on or around them.

The relationships found between attitude, subjective norms, perceived behavioral control, and intention confirmed the Theory of Planned Behavior (Ajzen, 1991) that attitude, subjective norms, and perceived behavioral control interacted with each other

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and also influenced intention. The positive influence of attitude on intention confirmed

Huang’s (2014) study that positive attitudes toward local food may increase consumers’ willingness to purchase local food. Subjective norms also showed a positive influence on intention, which was similar to Chang’s (2011) finding that consumers’ purchasing intention would be influenced by their families, friends, and colleagues’ opinions associated with their purchasing behavior. Whereas Peng (2011) indicated Taiwanese people’s food purchase would not be associated with affordability and accessibility, the finding of this study showed opposite result that the perceived behavioral control positively influenced the respondents’ intention to purchase locally grown food. Note that subjective norms had greater influence on intention compared to attitude and perceived behavioral control. Compared to existing literature, differences were found in the degree of the subjective norms’ effect on behavioral intention compared to the degree of effect of attitude and perceived behavioral control (Teng & Wang, 2015; Wu &

Chen, 2014). Subjective norm was the most influential factor within the three Theory of

Planned Behavior variables to predict intention in this study with it being less influential than attitude but more influential than perceived behavioral control in Wu and Chen’s

(2014) study. In contrary to the differences found in comparison to Wu and Chen’s

(2014) study, the findings in this study were supportive of Teng and Wang’s (2015) findings that subjective norms effect on purchase intention was higher than attitude.

However, the perceived behavioral control was not included in Teng and Wang’s (2015) study so no comparison of effect strengths between subjective norms and perceived behavioral control on intention can be made. Heinrichs et al. (2006) and Muk (2007) studied cultural differences in factors influencing consumption behaviors between

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Western and Asian consumers and found Asian consumers’ behavioral intention was highly influenced by social norms. This may be explained by the specific culture in

Eastern Asian countries that individuals are prone to weigh social views while making behavioral decisions (Heinrichs et al., 2006; Muk, 2007). Therefore, when the Theory of

Planned Behavior is used to conduct studies in Asian countries the effect of subjective norms should not be ignored.

Individuals’ demographic characteristics also influenced their knowledge, awareness, experience with food insecurity issues, attitude towards locally grown food, subjective norms, perceived behavioral control, and intention to purchase locally grown food. Demographic characteristics of having dependent children, being the decision maker on food purchases in the household, and city of residence (New Taipei City,

Taoyuan City, Hsinchu County, and Hsinchu City) when compared with Taipei City were found to be significant predictors on locally grown food purchasing intent. Individuals’ intention to purchase locally grown food increased when they (a) had dependent children, (b) were the decision-makers of food purchases in the household, (c) lived in

Taoyuan City or (d) Hsinchu City, but decreased when they lived in New Taipei City or

Hsinchu County.

The inter-correlations found between the food insecurity variables, Theory of

Planned Behavior variables, and demographic variables can be explained by Social

Cognitive Theory (Bandura, 1986). Anderson, Winett, and Wojcik (2007) indicated that demographic characteristics, including sex, age, and social economic status, may influence individuals’ behavior with possible regulation on their self-efficacy and social environment. Bandura’s (1986) theory and the findings of Anderson et al. (2007) can be

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used to explain the inter-correlations found in this study that food insecurity variables and Theory of Planned Behavior variables were influenced by demographic variables.

Prediction of Locally Grown Food Purchases

According to the results of the multiple linear regression, the significant predictors of intention to purchase locally grown food included (a) subjective norm, (b) perceived behavioral control, (c) knowledge, (d) awareness, (e) being the food decision-maker, (f) agricultural involvement levels of involved in agriculture for a living, (g) not involved in agriculture, but someone in my immediate family is when compared to someone with agricultural involvement of never been involved in agriculture and no one in my immediate family has ever been involved in agriculture, (h) city of residence of New

Taipei City, (i) Taoyuan City, (j) Hsinchu County, and (k) Hsinchu City when compared to someone living in Taipei City, and (l) area of residence of living in urban or suburban area outside of city limits when compared to someone living in downtown area in a city or town.

Chang’s (2011) study used the Theory of Planned Behavior to examine consumers’ intention to consume in organic restaurants and found consumers’ attitude, subjective norms, and perceived behavioral control positively influenced their intention to visit organic restaurants. Similarly, subjective norms and perceived behavioral control showed positive effects on predicting the general public’s intention to purchase locally grown food. However, the effect of attitude on intention was not significant in this study.

Note that the effect of perceived behavioral control increased when more variables were added into the model. Such a finding indicated that the effect of perceived behavioral control on intention was hindered without sufficient control of variables being included in the prediction model. According to Terry and Hogg (1996), subjective norms was

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considered as the weakest predictor of the behavior in the Theory of Planned Behavior model, compared to attitude and perceived behavioral control. In this study, the findings were almost opposite to Terry and Hogg’s (1996) study that subjective norms had the greatest influence on intention, while attitude did not influence intention significantly.

Such a strong impact that subjective norms had on influence intention can be supported by the findings of Heinrichs et al. (2006) and Muk (2007), which indicated a strong effect of subjective norms on a given behavior in Asian culture.

The influences of food insecurity variables on intention to purchase locally grown food were found significant in knowledge and awareness, while experience did not show a statistically significant effect on intention. Perceived knowledge showed a negative influence on intention, whereas awareness showed a positive influence on intention.

Such a finding was different from Tung’s (2008) and Cheng’s (2007) studies, which revealed the influences experience had on intention and decision-making of pro- agriculture behaviors. Huang and Lamm (in press) indicated individuals’ experience and awareness can potentially influence their behavior. In this study, although the effect of experience on intention faded in the best-fit prediction model, the positive effect of awareness on intention was significant, which supported the finding of Huang and

Lamm’s (in press) study. Interestingly, the effect of knowledge on intention became significant when demographic variables were added into the model and the significant effect of experience on intention diminished. This indicated that the significant effect of experience on intention may be mediated by demographic variables. Therefore, when demographic variables were controlled in the prediction model, the direct effect of experience on intention became insignificant.

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Specific demographic characteristics were significant predictors of intention to purchase locally grown food in this study. Compared to the residents with income lower than $10,000 NTD per month, those with income ranged between $10,000 and $19,999 tended to have greater intention to make locally grown food purchases. Being the food decision-maker in the household was another important factor which positively influenced the intention to purchase locally grown food. Interestingly, residents who were involved in agriculture for a living or who have no personal involvement in agriculture, but their immediate family is tended to have less intention to purchase locally grown food, when compared to those who have no personal agricultural involvement and no one in the immediate family is. City of residence also mattered. In comparison to residents living in Taipei City, residents of Taoyuan City and Hsinchu City tended to have better intention to purchase locally grown food, while residents of

Hsinchu County tended to have less intention to purchase locally grown food. Lastly, a positive impact of area of residence on intention to purchase locally grown food was found in residents living in urban or suburban area outside of city limits, compared to those living in downtown areas in a city or town.

The findings of the prediction model can be supported by Social Cognitive

Theory (Bandura, 1986) and the findings of Lin (2012) and Anderson et al. (2007) in which incorporated Social Cognitive Theory that behavior can be regulated by personal factors, including demographic characteristics, attitudes, perceptions, and self-efficacy to purchase locally grown food, and environmental factors, including subjective norms, observation of the social environment, and environmental issues. In this study, demographic characteristics, attitudes, subjective norms, and perceived behavioral

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control were considered as the personal factors, while subjective norms, perceived behavioral control, and food insecurity issues were considered as the environmental factors. The findings of this study not only showed the interaction and inter-correlation between the personal factors, environmental factors, and behavior, a significant prediction model using the Theory of Planned Behavior as the base and incorporating additional external factors was also developed by integrating Social Cognitive Theory into the model. The concluded conceptual model with significant prediction factors can be viewed in Figure 5-1.

Implications and Recommendations

The demographics of the respondents revealed the possible characteristics of online survey respondents sampled using opt-in approach in that they are primarily living in the urban areas of major cities, lack agricultural experience, are highly educated, and have average income levels (National Statistics, Republic of China,

2015). The majority of respondents were married females who were relatively young with no dependent children. These findings imply the possible characteristics of online survey respondents living in the Northern Region of Taiwan recruited using panels and can be used to inform future studies.

While evidence of low public awareness of food insecurity issue in Taiwan was lacking, the findings of this study provided information that can fill this gap (Ministry of

Foreign Affairs, 2013; Peng, 2011; Tsai, 2011). Most respondents perceived they lacked food insecurity and agricultural knowledge but had a fair level of actual knowledge related to food insecurity and agriculture, which implied a need for educational information about agriculture to connect what they actually know and what they perceive they know among the respondents. Such a disconnect between perceived knowledge

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and actual knowledge was also found when exploring the relationship between perceived knowledge and awareness that the respondents’ perceived knowledge level was negatively associated with their food insecurity awareness score. However, the awareness questions were not fully developed to reflect each of the items listed in the perceived knowledge level measurements. Question modification in both perceived knowledge and awareness measurements may be needed to better examine the case.

The findings of the food insecurity experiences were highly aligned with the news coverage and critical weather event at the time of data collection (Chou, 2015; Mullen,

2015). This may imply that the respondents’ answers were influenced by the information in the surrounding environment, while it also implied a public concern about human health based on the coverage of food safety issues. Additionally, such findings revealed opportunities for extension practitioners who are concerned about the local agricultural industry and food insecurity to draw public attention to agricultural issues and seek solutions from public support of local agriculture.

The respondents showed positive attitudes toward locally grown food in Taiwan, which supported the findings of previous researchers (Chang, 2012; Huang, 2014; Ou et al., 2011). This implies that the respondents were still confident in food produced in

Taiwan. The order of the attitude items implies the respondents were most confident in the taste of Taiwan’s locally grown food, but least confident in the safety of locally grown food. The respondents’ perceived importance of agriculture was high in that they perceived agriculture could benefit humans and society in a variety of ways. However, to compare the responses received as very important and extremely important, it was higher in agriculture’s benefits to human health but lower in agriculture’s benefits to job

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opportunities. Such a finding implied that the respondents may see and understand the connection between agriculture and food, but they do not see agriculture as a promising career with job opportunities.

Important individuals around the respondents showed great influence on the respondents’ behavior of purchasing locally grown food (Chang, 2011; Lien & Chen,

2010). While more respondents agreed or strongly agreed about their family’s influence on their locally grown food purchases, less responses were received in colleagues’ influence on their locally grown food purchases (Wu & Chen, 2014). Such a finding implied that family may have greater power to alter the respondents’ behavior decisions.

Respondents’ perceived behavioral control in availability, affordability, and accessibility of locally grown food was high in this study. Respondents agreed or strongly agreed that locally grown food was affordable, this finding implies that the respondents were less concerned about food price and did not perceive food price would ever be problematic (Peng, 2011).

This study revealed that about 85% or more respondents indicated they would purchase locally grown food in the next 12 month regardless of types of food. This finding implied the respondents were not only willing to support locally grown food, but also perceived they would be able to purchase any type of locally grown food. However, some types of locally grown food may not be fully grown by local farmers to fulfill the demand (COAEY, 2014a). Such a dissonance in the perception and fact revealed a knowledge gap within the respondents. Moreover, this also implies that respondents may believe what they are purchasing is locally grown food, but it is actually not.

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Additional efforts should be taken not only towards educating people about food sources but also towards revitalizing local agricultural production to fulfill the demands.

The inter-correlation found between demographic characteristics, knowledge, awareness, and experience of food insecurity issues, and their attitude towards locally grown food, and subjective norms, perceived behavioral control, and intention to purchase locally grown food indicated the general public’s intention to make locally grown food purchases would be influenced by these listed variables (Anderson et al.,

2007; Chang, 2011; Cheng, 2010). The strength of the relationships between variables and various influential patterns in each demographic variable revealed the existence of cognitive and experiential differences among the respondents with different demographic characteristics (Bandura, 1986).

The regression model to predict intention to purchase locally grown food revealed the valid predictors and their strength of influencing intention. The greatest effect size of subjective norms implied that the action (purchasing locally grown food) of the general public in the Northern Region of Taiwan would take may be heavily influenced by the opinions of their important others, particularly family. While attitude was not a significant predictor of intention to purchase locally grown food from Model 1 to Model 2 till Model 3, the effect of experience on intention diminished when demographic variables were added to the model. Such findings may imply a special cultural case exists in terms of Taiwan that the population of interest’s (the general public in the Northern Region of Taiwan) purchases of locally grown food tended to be strongly influenced by a social norm among individuals’ important others in their lives

(Heinrichs et al., 2006; Muk, 2007; Teng & Wang, 2015; Terry & Hogg, 1996; Wu &

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Chen, 2014). As for the insignificant effect of attitude on predicting intention to purchase locally grown food, it may imply a need to explore possible factors hindered the effect of attitude on the behavioral intention. Moreover, the finding that the effect of experience faded in Model 3 implied that demographic variables may explain the change in intention more than experience. Individuals’ personal background may influence their experiences associated with the behavior. For example, individuals who live in the capital with high income may consider food amount, price, and access less as concerns due to their easy access to sufficient amounts of food and a sufficient income to pay for the food (Peng, 2011).

The significant demographic variables revealed some interesting phenomena that (a) the individuals having direct and long-term involvement in agriculture or indirect involvement in agriculture would be less likely to purchase locally grown food when compared to the individuals who have never been involved in agriculture either directly or indirectly; (b) the residents living in city/county with observable rural and urban lives

(i.e., New Taipei City, Taoyuan City, Hsinchu County, and Hsinchu City) would show changes in intention to purchase locally grown food, compared to the residents of Taipei

City; and (c) the individuals living in an area between rural and urban areas have higher tendency to purchase locally grown food in comparison to those living in downtown areas. These findings may imply that (a) having direct and long-term involvement in agriculture or indirect involvement in agriculture may provide individuals easy access to locally grown food and led to a decreased intention to purchase locally grown food, when comparing to individual without any direct or indirect agricultural involvement; (b) residents of Taoyuan City (a satellite city of Taipei City) and Hsinchu City (a highly

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industrialized city) may tend to purchase more locally grown food due to their observability of both rural and urban lives in the surrounding areas, while residents of

New Taipei City (a satellite city of Taipei City) and Hsinchu County (relatively rural) may have less tendency to purchase locally grown food due to less income level to support their living expenses (New Taipei City) or easy access to the agricultural industry

(Hsinchu County), compared to residents of Taipei City where residents have limited access to the agricultural industry and high income level to purchase food regardless of sources; and (c) residents living in an area between rural and urban areas may have higher chance of observing agriculture, which may lead to a higher chance to purchase locally grown food when compared to residents living in downtown areas. Future studies may be needed to explore the effect of observability of agriculture on individuals’ intention to purchase locally grown food to support the speculation in this study.

Online Survey Opportunities

Online surveys have been widely used in Taiwan as a social science research method since the increased use of the Internet in the Taiwanese population (Li, 2004).

However, the use of online surveys is still problematic in reaching older populations. In this study, even if the data were weighted to improve the representativeness of the responses, a lack of respondents aged 70 and older was a problem because no data were received to weight. Currently, about 800,000 people in the Northern Region were aged 70 and older, which was almost 10% in the amount of population of interest in this study (Ministry of Interior, 2015). Therefore, alternative approaches should be used or even developed in order to improve the reachability to the older population.

The findings of this study revealed that younger married females tend to be reached and willing to respond to online surveys. In addition, most of them indicated

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they are the decision-makers of food purchases in a household. Therefore, studies focused on a population with similar characteristics to those mentioned above may consider using online survey for data collection.

Extension and Education Opportunities

The findings of this study shed light on educational information about agriculture in Taiwan associated with national food insecurity. The respondents showed relatively low knowledge and a fair level of awareness (actual knowledge) of food insecurity issues, which revealed an information gap between what people perceived they know and what they actually know. The respondents perceived they know more about food insecurity issues with higher personal relevance (e.g., food safety, food price fluctuation). Additionally, while the respondents tended to know more about facts associated with agriculture in a bigger spectrum (e.g., farm land decrease, impact of climate change on agriculture, food safety), they know less about specific facts related to agricultural production, such as what types of food can be fully locally produced. As a result, educational programs should be developed based on personal relevance to the target audience (Huang & Lamm, in press). More specifically, the educational materials could be designed beginning with food safety issues and then gradually provide information with increased depth and complexity about agriculture (e.g., food production process). Another educational opportunity would be to use the timing wisely. As the results of this study might be impacted by the severe weather event, it may imply that the respondents were more aware of food related issues. Extension should use issue outbreaks, such as typhoons, as opportunities to educate the general public with credible and trustworthy information about agriculture when they are more aware of the issues.

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Extension practitioners should also be aware that the general public may have a relatively negative perception about agriculture as a career option since many of them did not see the job opportunities provided by agriculture. As the agricultural labor force has been continuously decreasing over time, extension should collaborate with the government to recruit more young laborers into the agricultural industry in order to rejuvenate the industry. Since the majority of the respondents did not see agriculture’s contribution to job opportunities, extension should provide information about agriculture related jobs including and beyond labor-intensive field positions to not only fill the gap of people’s limited understanding of agriculture-related jobs, but also reveal the diversity in agriculture-related jobs to enhance people’s interest in agricultural involvement. In addition, agriculture revitalization programs can be developed by encouraging elder farmers to pass agricultural knowledge and skills to the younger generation.

Another disconnect in cognition about agriculture existed in the general public’s perceived availability, affordability, and accessibility of locally grown food and the actual availability, affordability, and accessibility of locally grown food. The residents in a highly urbanized region may tend to be less concerned about food price if they have a high income; however, they may be less likely to know or be aware of the access and availability of locally grown food. A knowledge gap was identified in availability of locally grown food since the majority of the respondents intended to purchase locally grown food, while some of the food items may not be produce locally in a sufficient amount.

Moreover, the situation may be that the general public perceived they are purchasing locally grown food but it is actually imported. Extension practitioners should not only fill the knowledge gap in the general public by providing the correct information and

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educating the general public to learn about food sources before purchasing, but also develop strategies to increase local production to fulfill the demands and further increase the national food self-sufficiency rate. Extension practitioners may work with various media, including television, newspaper (online and in print), videos, and social media, to create story-telling styled narratives covering growers’ challenges to compete with imported food and the actual availability of locally grown and imported foods in the market that may better draw audiences’ attention and provide correct agricultural information to them. By working with various media channels, both older (tend to use mass media) and younger generations (tend to use online media) can be covered

(Taiwan Communication Survey, 2014). Therefore, this may further result in higher tendency of family influences on locally grown food purchasing intention. Once consumers and community support for locally grown food is established they can combine efforts to develop agriculture revitalization programs, wherefore locally grown food production can be increased which can ultimately increase the national food self- sufficiency rate and alleviate the food insecurity issues in Taiwan.

For extension practitioners who would like to promote locally grown food, targeting specific audiences may lead to increased tendency of buy-in. Note that the demographic characteristics which may positively influence individuals’ intention to purchase locally grown food included (a) being the food decision-maker, (b) city of residence as New Taipei City, (c) Taoyuan City, and (d) Hsinchu City when compared to someone living in Taipei City, and (e) area of residence as living in urban or suburban area outside of city limits when compared to someone living in downtown area in a city or town. Extension practitioners should consider recruiting participants characterized as

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above in order to maximize their intention to purchase locally grown food. This can be reached by emphasizing the marketing areas at urban or suburban areas outside of city limits of Taoyuan City and Hsinchu City, while providing promotional programs at the major local supermarkets or traditional markets to cover consumers in various income levels (typically high for consumers shopping at supermarkets, low for those shopping at traditional markets) and major food decision-makers.

Marketing Opportunities

The findings of this study can also provide hints to local growers and agricultural business owners for marketing. Again, similar to the recommendation to extension practitioners for locally grown food promotion, factors which may positively influence individuals’ intention to purchase locally grown food should be considered. In addition, consumers’ awareness of food insecurity issue may also influence their intention to purchase positively. Based on the development of the awareness measurement in this study, it can also be interpreted as actual knowledge of food insecurity issues.

Therefore, facts about food insecurity issues can be provided in the promotion strategy.

What has to be noticed is the food insecurity fact should be provided in a personally relevant manner to the consumers. For example, the growers and agricultural business owners can promote food produced in Taoyuan City to consumers living in Taoyuan

City by adding a short production story about the food product’s production process and costs. By understanding more about the agriculture production and even the sale competition between imported food and locally grown food, it is expected that the consumers’ intention to purchase locally grown food would increase. Moreover, the growers and agricultural business owners can consider collaborating with restaurants selling locally grown food or branding as green restaurants by contracting ingredient

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provision to the restaurants. The consumers of these restaurants may have higher intention to visit green restaurants since they tend to take their important others’ opinions into consideration selecting a green restaurant (Chang, 2011; Chou et al.,

2009; Lien & Chen, 2010). If a contract between growers/agricultural business owners and green restaurants is established, the sale of locally grown food is expected to increase.

Research Opportunities

National food insecurity issues have not been studied widely in Taiwan. This study provided an overview of the general public’s knowledge, awareness, and experience with food insecurity issues in Taiwan, as well as possible solutions to the issue by increasing the general public’s purchasing of locally produce food. This study explored the current situation in the Northern Region of Taiwan, so the findings were not representative of the overall population of Taiwan. Further study should be conducted in other regions of Taiwan to explore the situation in the relatively less urbanized regions.

Additionally, comparison of regional differences can be further studied by comparing the results collected from different regions of Taiwan.

Due to the lack of an existing instrument, the instrument used in this study was researcher-developed. Some items and measurements may need to be further modified to strengthen the rigor of the study. For example, the arrangement of the awareness measurement did not fully connect with the perceived knowledge and experience measurements. Such a situation may weaken the explanation of the findings. Future effort can be made to develop a food insecurity awareness tools to create for a stronger awareness index to further analyze the situation.

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The results of this study might be impacted by the severe typhoon event during the data collection process. A similar study may be conducted during the season without severe weather events to explore the general public’s opinions under normal circumstances. Moreover, a longitudinal study could be conducted to explore the changes in people’s opinions and in the change of awareness of food insecurity issues over time. The findings of this study can also be used as the base of a qualitative study on food insecurity issues in Taiwan to collect and explore Taiwanese people’s opinions in depth.

Lastly, examinations of extension’s educational programs and growers and agricultural business owners’ promotional programs should also be conducted to confirm the effectiveness of the recommended strategies. For example, these programs should be evaluated by collecting feedback from the participants or consumers covering their attitude, knowledge, and even behavioral changes associated with locally grown food. Food insecurity in Taiwan is a complicated and complex issue which may need efforts from various sources, including government, extension, universities, agricultural industry professionals, growers, social activist groups, and beyond. Since disconnects exist between the general public and agriculture, agriculture’s role in society should be redefined and redeclared with the goal of enhancing the community and society engagement to achieve sustainability within the industry. While the world has been looking for strategies and solutions to feed almost 10 billion people in 2050, the food insecurity situation in Taiwan should be seriously considered as an issue in need of being solved.

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Summary

This study was conducted based on the Theory of Planned Behavior and the

Social Cognitive Theory. According to the conceptual model, the findings showed that the respondents had low knowledge, fair awareness, and limited experiences of food insecurity issues, but had positive attitudes and perception of locally grown food and high intention to purchase locally grown food. However, such a high intention of purchasing locally grown food was significantly influenced by individuals’ subjective norms and perceived behavioral control of purchasing locally grown food, in additional to their knowledge and awareness of food insecurity issues and demographic characteristics of a) income level of $10,000-19.999 when compared to someone with income lower than $10,000, b) being the food decision-maker, c) agricultural involvement levels of involved in agriculture for a living and h) not involved in agriculture, but someone in my immediate family is, when compared to someone with agricultural involvement of never been involved in agriculture and no one in my immediate family has ever been involved in agriculture, d) city of residence of Taoyuan

City, e) Hsinchu County, and f) Hsinchu City when compared to someone living in

Taipei City, and g) area of residence of living in urban or suburban area outside of city limits when compared to someone living in downtown area in a city or town.

The findings of this study can be useful to extension practitioners, agriculture business owners, and researchers. Credible, trustworthy, and correct information about agriculture and food insecurity should be provided to the general public with inclusion of problem-solving strategies to alleviate a national food insecure situation, such as supporting locally grown food through purchases.

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Figure 5-1. Concluded conceptual model of support for locally grown food in Taiwan.

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APPENDIX A FOOD INSECURITY AND SUPPORT OF LOCALLY GROWN FOOD SURVEY (ENGLISH VERSION)

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BIOGRAPHICAL SKETCH

Pei-wen Huang was born and raised in Taipei City, Taiwan. She grew up and completed her education in Taiwan until receiving her Bachelor of Science degree in horticultural sciences with a focus on crop science from the National Taiwan University in 2006. Upon degree completion, Pei-wen found her passion in horticulture and decided to pursue a master’s degree in the United States in horticultural sciences. She enrolled in a master’s program in the Horticultural Sciences Department at the

University of Florida in fall 2006 with a focus on sustainable weed management. Her thesis study was entitled “Optimal conditions for buckwheat [Fagopyrum esculentum

Moench] production as a cover crop for weed suppression in Florida.” She earned her

Master of Science degree in summer 2009 and then continued working as a research assistant in the Horticultural Sciences Department of the University of Florida.

Pei-wen’s passion for horticulture continued while she accepted the offer of a doctoral program in the Horticultural Sciences Department in the University of Florida at the Gulf Coast Research and Education Center in spring 2010. She then moved to

Balm, Florida to work on a strawberry transplant production study. During her time in

Balm, she was exposed to Extension while working with her adviser and the research and education center. Assisting with extension-related presentations and events sparked her interest in extension and outreach services. Through her experiences she realized the need and importance of science communication and started to seek a role in the industry and academics in order to apply her knowledge. After her self-seeking process and communication with extension professionals, Pei-wen made the decision to transfer to the Department of Agricultural Education and Communication at the

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University of Florida in fall 2013 to continue her doctoral program focused on extension education.

During the time working on her doctoral program in extension education, Pei-wen has worked as a graduate assistant in the Center for Public Issues Education in

Agriculture and Natural Resources on various projects, including issues related to water, invasive species, and immigrants. She had worked with a county Extension agent in commercial horticulture as an intern on program development, preparation, delivery, communication, and evaluation. She has enjoyed her extension work and has dreamed about becoming a county Extension agent after graduation in order to be a local service provider and directly apply what she has learned in the real-world setting.

She received her Ph.D. from the University of Florida in agricultural education and communication in the fall of 2015 and expects to expand the exposure of the Extension service to more audiences and provide extension programs with enhanced effectiveness and greater impacts to the community to make the environment more sustainable.

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