This study seeks to examine consumer intention to re-consume organic food in Indonesia from a psychological standpoint using the Theory of Planned Behavior (TPB). In this study, new constructs were included, namely perceived sensory appeal, egoistic motive, and warm glow. Responses were collected from 337 consumers through online surveys and analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The results of the analysis show that the TPB constructs partially support the intention to re-consume organic food, as well as the attitudes and subjective norms. The outcomes added that the new construct in TPB is known to be able to increase the predictive power of the proposed framework and shows the importance of perceived sensory appeal, egoistic motive, and warm glow in the estimation of sustainable organic food consumption.
Citation: Dhika Cahyasita, Irham, Jamhari. Intention to re-consume organic food: Sensory attributes, egoistic motive, and warm glow in the extended TPB[J]. AIMS Agriculture and Food, 2021, 6(4): 891-919. doi: 10.3934/agrfood.2021054
| [1] | Sharon L. Casapulla, Gloria Aidoo-Frimpong, Tania B. Basta, Mario J. Grijalva . Zika virus knowledge and attitudes in Ecuador. AIMS Public Health, 2018, 5(1): 49-63. doi: 10.3934/publichealth.2018.1.49 |
| [2] | Paulina Januszko, Ewa Lange . Nutrition, supplementation and weight reduction in combat sports: a review. AIMS Public Health, 2021, 8(3): 485-498. doi: 10.3934/publichealth.2021038 |
| [3] | Dimitris Zavras . A cross-sectional population-based study on the influence of the COVID-19 pandemic on incomes in Greece. AIMS Public Health, 2021, 8(3): 376-387. doi: 10.3934/publichealth.2021029 |
| [4] | Laura Gonzalo-Ciria, Marta Pérez De Heredia-Torres, María Isabel Vidal-Sánchez, María José López-de-la-Fuente, Elisa Bullón-Benito, Ana Poveda-García, Mariana Ortiz-Piña, María Cristina Ruiz-Garrós, Ana Gascón-Catalán . Loss of productivity among caregivers of dependent family members. AIMS Public Health, 2025, 12(2): 451-469. doi: 10.3934/publichealth.2025025 |
| [5] | Carmen Lok Tung Ho, Olivia Oligbu, Fatma Asaid, Godwin Oligbu . Does norovirus induce acute hepatitis?. AIMS Public Health, 2020, 7(1): 148-157. doi: 10.3934/publichealth.2020013 |
| [6] | María D Figueroa-Pizano, Alma C Campa-Mada, Elizabeth Carvajal-Millan, Karla G Martinez-Robinson, Agustin Rascon Chu . The underlying mechanisms for severe COVID-19 progression in people with diabetes mellitus: a critical review. AIMS Public Health, 2021, 8(4): 720-742. doi: 10.3934/publichealth.2021057 |
| [7] | Heitham Awadalla, Fateh El-Samani, Mohammed A. Soghaier, Mahgoub Makki . Risk Factors Associated with the Development of Tuberculosis Among HIV-Infected Patients in Khartoum in 2010. AIMS Public Health, 2015, 2(4): 784-792. doi: 10.3934/publichealth.2015.4.784 |
| [8] | Junji Takaya . Small for Gestational Age and Magnesium: Intrauterine magnesium deficiency may induce metabolic syndrome in later life. AIMS Public Health, 2015, 2(4): 793-803. doi: 10.3934/publichealth.2015.4.793 |
| [9] | Taija Finni, Marja Uusi-Vähälä, Arto J. Pesola, Ritva S. Taipale . Do Running and Strength Exercises Reduce Daily Muscle Inactivity Time?. AIMS Public Health, 2016, 3(4): 702-721. doi: 10.3934/publichealth.2016.4.702 |
| [10] | Ehsan Shoohanizad, Ata Garajei, Aida Enamzadeh, Amir Yari . Nonsurgical management of temporomandibular joint autoimmune disorders. AIMS Public Health, 2019, 6(4): 554-567. doi: 10.3934/publichealth.2019.4.554 |
This study seeks to examine consumer intention to re-consume organic food in Indonesia from a psychological standpoint using the Theory of Planned Behavior (TPB). In this study, new constructs were included, namely perceived sensory appeal, egoistic motive, and warm glow. Responses were collected from 337 consumers through online surveys and analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The results of the analysis show that the TPB constructs partially support the intention to re-consume organic food, as well as the attitudes and subjective norms. The outcomes added that the new construct in TPB is known to be able to increase the predictive power of the proposed framework and shows the importance of perceived sensory appeal, egoistic motive, and warm glow in the estimation of sustainable organic food consumption.
Noise-induced hearing loss (NIHL) is one of the most common occupational disease experienced across the world in occupational environments [1] and the second most common cause of acquired hearing loss after presbyacusis [2]. It has been estimated that about 500 million individuals might be at increased risk of developing NIHL [3].
There is a large individual variability in susceptibility to the damaging effects of noise; after exposure to similar level of noise, some subjects develop different level of NIHL, so has been proposed that NIHL is a complex disease that is influenced by interaction of environmental and genetic factors [4]. Environmental risk factors causing hearing loss include noise, vibration, heat, chemicals such as organic solvents and heavy metals, ototoxic drugs, infections, nutrient disturbances, smoking, high blood pressure and cholesterol levels and possibly pigmentation [4],[5].
Little is known about the involvement of genetic factors that influence NIHL in human. Several NIHL susceptibility genes have been suggested, such as, genes encoding for the antioxidant systems, potassium ion channels, heat shock proteins, and the signaling function of the immune system [6]. Oxidative stress genes, such as glutathione S-transferase, (GST); glutathione peroxidase (GPX1); glutathione reductase (GSR), superoxide dismutases (SOD), catalase (CAT), and paraoxonase (PON) [6] are obvious candidate genes for NIHL [7]. Numerous studies have shown that high-intensity noise exposure causes mechanical or metabolic changes in the cochlea which lead inner ear damage [8]. The metabolic changes are caused mainly by increase in free radical species (FRS) that play a primary role in NIHL [9]. The harmful effects of FRS are generally prevented by endogenous antioxidants. Tripeptide glutathione (GSH), a major intracellular antioxidant, is proven to detoxify free radicals and to prevent NIHL [10]. The most important antioxidant enzymes in the cochlea that are involved in GSH metabolism are glutathione S-transferase (GST), glutathione peroxidase (GPX1), and glutathione reductase (GSR) [10]. GST enzymes catalyze conjugation of GSH with free radicals and have an important role protecting the cochlea [11]. GST classified into several gene classes (GSTA, GSTM, GSTP, GSTT, GSTZ, GSTS, GSTK, GSTO) [5]. In humans, there is genetic variability of GSTT1 and GSTM1. Up to 50% of the Caucasian population has null genotype for GSTM1 [12], while 25–40% of the Caucasian population are null for GSTT1 gene [13]. Individuals with the null genotype for either GSTT1 or GSTM1 cannot conjugate toxins specific to these enzymes, so they may be at increased risk of developing NIHL [14].
There are limited and inconsistent results about association between variation in GST genes and susceptibility to NIHL. Rabinowitz et al. showed that among 58 noise-exposed American workers, GSTM1 null individuals had lower amplitudes of high frequency otoacustic emissions compared to individuals possessing the gene. However their finding lacked sufficient power and this may be a spurious finding [14]. In later study involving 194 Chinese workers who exposed to occupational noise, Yang et al. suggested that GSTT1 null individuals might be more susceptible to NIHL [15]. Lin et al. found that among 58 noise-exposed workers in Taiwan, individuals carrying all genotypes with GSTM1 null, GSTT1 null, and GSTP1 I1e105/I1e105 might be more susceptible to the effects of noise [10]. However in much more comprehensive study among 10% most susceptible and 10% most resistant to noise subjects selected from 1200 Swedish workers, an association between GSTT1, GSTM1, and GSTP1 could not be confirmed [11]. Palodetto et al. found no significant association between GST gene variants (GSTT1 and GSTM1) and ototoxicity of aminoglycosides, which seems to involve similar oxidative stress mechanisms [16]. In addition to contradictory results in various studies, the effect of genetic factors on susceptibility of NIHL can only be regarded as valid when they have been replicated in an independent population [17]; so, the present study investigates the association between the deletion polymorphism in the GSTT1 (rs1049055) and GSTM1 (rs10712361) genes and susceptibility to NIHL in Iranian population.
This case-control study was performed in accordance with the guidelines in the Declaration of Helsinki and with approval from the medical ethics committee of Shahid Sadoughi University of medical sciences, Iran. An informed consent was obtained from all study subjects.
The present study was conducted on male workers from 7 tile and ceramic factories in Yazd, a center province of Iran. Factories which had high stability of the workforce and had periodic noise level measurements were selected by simple random sampling from all tile and ceramic factories in Yazd (n = 30). In each factory subjects who had been employed for at least 3 years and exposed to hazardous noise (≥ 85 dBA) were selected by simple random sampling [11]. Noise level was extracted from the result of measurements routinely performed in the factories by industrial hygiene incorporations.
Those with previous history of acoustic trauma, congenital or familial hearing loss, and ototoxic drug consumption, positive medical history of diabetes mellitus, hypertension, head trauma, head surgery, chronic otitis media, conductive hearing loss in pure-tone audiometry, previous exposure to organic solvents or loud noise in previous or second job or in non-occupational form, and family history of deafness were excluded from the study.
A questionnaire including age, duration of employment in current job, smoking and alcohol consumption and medical history was filled for each subject.
After usual otoscopic examination, pure-tone audiometry (using clinical audiometer: Interacoustic, AC40, Denmark, headphone: TDH39) was performed for the subjects in an acoustic chamber meeting the requirements of the American National Standards Institution (ANSI) 2004 by an expert audiologist (blinded to the study) [12]. Air conduction was assessed at 250, 500, 1000, 2000, 3000, 4000, 6000, and 8000 Hz frequencies and bone conduction at 250–4000 Hz frequencies for each ear.
After considering inclusion and exclusion criteria, according to the result of audiometry, subjects were classified into two groups: from 80 NIHL subjects, 73 individuals with audiograms suggestive NIHL as a case group (8 were excluded due to diabetes mellitus, conductive hearing loss, familial hearing loss and history of head trauma) and from total 90 subjects, 87 normal hearing individuals enrolled in the study as controls [13], (3 were excluded due to conductive hearing loss and diabetes mellitus). Their workday was approximately 8 hours per day. Most workers did not use hearing protective devices (ear plugs) and a few workers used ear plugs very irregularly.
Venous blood samples for DNA extraction were also collected in EDTA tubes at the workplace and placed immediately container and then transported on dry ice to the laboratory. This extraction was carried out under sterile conditions and under the laminar hood. DNA extraction from blood was performed using a DNA extraction kit called Bio Flux (Shanghai Beiyi Bioequip Information Co., china). The next step was DNA extraction for use in the polymerase chain reaction. The purpose of the multiplex PCR was to amplify the genomic DNA regions containing GSTT1 (Forward primer: 5′ TTCCTTACTGGTCCTCACATCTC 3, Reverse primer: 5′ TCACCGGATCATGGCCAGCA 3′), and GSTM1 (Forward primer: 5′ GAACTCCCTGAAAAGCTAAAGC 3′, Reverse primer: 5′ GTTGGGCTCAAATATACGGTGG 3′) in addition to the B-globin gene as control. At this stage, 15 µl Master Mix 2x (cinnagen, Iran) (which itself contains 2mM MgCl2), was made up of a total volume of 30 µl: containing 100 ng of genomic DNA and 12.5 pM each of the forward and reverse GSTT1, GSTM1, and B-globin primers.
The PCR reaction was carried out in 3 steps, one cycle of 94 °C for 5 minutes followed by 30 cycles of 94 °C for 1 min, 62 °C for 1 min, and 72 °C for 1 min and the final step was 72 degrees for 5 minutes. The PCR product was run in 2% (w/v) agarose gel and the bands were visualized with UV light.
Three bands should be observed: The B-globin band to be observed in all wells is 268 bp, GSTT band is 480 bp and GSTM band is 219 bp. Both GSTM and GSTT bands may exist or have been deleted, creating four different patterns: T+ M+, T+ M−, T− M+ or T− M−.
Data was analyzed by SPSS version 18 (SPSS, Inc., Chicago, IL). One-Sample Kolmogorov-Smirnov test was applied to test normality of study variables. Independent Student's t-test and Mann-Whitney test were used to compare continuous variables between groups. The frequency of polymorphism was compared between groups by chi-square test and Fisher's exact test and odds ratios with corresponding 95% confidence intervals (95% CI) were calculated with Mantel-Haenszel method. P-value ≤ 0.05 was considered statistically significant.
A total of 160 male subjects that comprised 73 individuals with audiograms suggestive NIHL as a case group and 87 normal hearing individuals as a controls participated in this study. Table 1 presents the demographic and personal characteristics of the study subjects.
| Case group (n = 73) | Control group (n = 87) | P-Value | |
| Age (years)* (Mean±SD) | 35.12 ± 3.85 | 34.71 ± 4.21 | 0.07 |
| Employment (years)† (Mean±SD) | 6.40 ± 2.39 | 6.37 ± 1.72 | 0.90 |
| Noise exposure (TWA) dBA† (Mean±SD) | 90.14 ± 2.59 | 89.72 ± 2.32 | 0.26 |
| Smoking‡ 9N (%)] | 19 (26.00%) | 14 (16.10%) | 0.09 |
Note: *Student's
DownLoad:
CSV
Null GSTT1 and null GSTM1 were found in 33 persons (20.6%) and 54 individuals (33.8%) of the study population, respectively. The frequency of null GSTT1 and GSTM1 genotypes and interaction between these genes as well as the comparison of the results among NIHL and control groups are shown on table 2. Null GSTT1 and GSTM1 genotypes were more frequent in NIHL group but no significant statistical difference was seen in NIHL and control groups.
| Genotypes | Case group n (%) | Control group n (%) | p-value | 0R (95% CI) |
| GSTT1 | ||||
| Normal genotype | 57 (78.1) | 70 (80.5) | 0.43 | 1.08 (0.72–1.61) |
| Null genotype | 16 (21.9) | 17 (19.5) | ||
| GSTM1 | ||||
| Normal genotype | 45 (61.6) | 61 (70.1) | 0.17 | 1.22 (0.87–1.71) |
| Null genotype | 28 (38.4) | 26 (29.9) | ||
DownLoad:
CSV
No significant interaction between GSTT1 and GSTM1 genotypes was found (P-Value > 0.05) (Figure 1).
The aim of this study was to assess that genetic variability of GSTT1 and GSTM1 is associated with susceptibility to NIHL in Iranian population.
It seems that many factors play a role in NIHL including genetic and environmental factors. Subjects who developing NIHL after exposure to noise are often exposed to many other risk factors that interact with each other and/or with genetic factors [14].
This study did not detect that the genetic variability of GSTT1 and GSTM1 affect on susceptibility to noise induced hearing loss. There are many controversial studies on association variations in oxidative stress genes and susceptibility to NIHL. Carlsson et al. analyzed genetic polymorphism in the 10% most susceptible and 10% most resistant extremes of 1200 Swedish noise-exposed workers to investigate whether genetic variation is associated with susceptibility to NIHL. In their study no significant differences were found between 103 noise-susceptible and 114 noise-resistant Swedish workers from the point of view of GSTM1 and GSTT1 polymorphism [6]. Palodetto et al. showed that polymorphism in GSTM1 and GSTT1 have no influence on ototoxicity of aminoglycosides, which seem to involve similar oxidative stress mechanis like NIHL [14]. Rabinowitz et al. analyzed polymorphism status for GSTM1 and GSTT1 in 58 factory workers [9]. They found that carriers of GSTM1 gene had better high frequency otoacoustic emission (OAEs) compared to GSTM1 null individuals but they found no significant effect of GSTM1 with pure tone audiogram. On the other hand GSTT1 did not show a protective effect. Their study lacks sufficient power due to small sample size. On the other hand, in a study in China, there was no significant relationship between GSTM1 gene deletion NIHL but the results suggested that GSTT1 polymorphism might play an important role in the development of NIHL in Chinese workers and the individuals with the GSTT1 null genotype might be more susceptible to NIHL [15] while in another study on Chinese workers, individuals with the GSTM1 null genotype had a statistically significantly increased risk of NIHL [22]. Study on 53 Taiwan male workers showed that GST polymorphism may modify the susceptibility to NIHL and that individuals carrying all genotypes with GSTT1 null, GSTM1 null, and GSTP1 Ile(105)/Ile(105) are more susceptible to NIHL [5].
The findings of study on Brazilian subjects (107 subjects with NIHL, 44 with other causes of hearing loss and 104 controls) suggest effects of GSTT1 and GSTM1 polymorphism on the risk of NIHL [2]. In study conducted by Manche and et al. on 220 subjects with presbycusis, gene polymorphisms of GSTT1/M1were found to contribute significant risk to presbycusis [23].
Several studies showed that antioxidant system is activated after noise exposure. It seems that noise exposure levels are important in activation of this system. So, it is possible in studies that did not find association of GST gene and NIHL, like our study, the noise exposure levels to which the majority of study workers have been exposed over the years did not reach the critical level needed to activate the antioxidant system, and therefore differences in their antioxidant systems are unlikely to show up in their findings. However, it is possible that difference exists when subetaoups (noise exposure levels, noise exposure times) be evaluated separately [6].
Our results showed that the observed frequency of null GSTT1 and null GSTM1 were 20.6% and 33.8%, respectively. The 20.6% frequency of null GSTT1 is on the low end of the range of 19–58% reported in some Asian populations also the 33.8%, frequency of null GST M1 is of the range of 28–63% reported in some Asian populations [5]. 25 to 40% of the European population has GSTT1 deletions also GSTM1 gene deletions have been reported up to 50% of European population [3].
Our study has several limitations. First of all, it was a cross-sectional study, and may therefore distort the association due to the healthy worker effect, and does not allow demonstration of a causal relationship. Secondly, this study lacks sufficient power due to small sample size. NIHL has complex nature that is influenced by interaction of environmental and genetic factors [14]; so many other environmental risk factors can have a confusing effect on this relationship, such as potential influence of length of time that the subjects have been exposed to non-occupational noisy conditions, commitment to using hearing protection devices at workplace and etc., As well as other risk factors (e.g., obesity, diet) have not been analyzed. A study conducted in 2006, suggested that to get better results on studies on NIHL susceptibility genes, 10% of the subjects with the worst hearing thresholds as susceptible to NIHL workers and 10% of the subjects with the best hearing thresholds as resistant to noise workers should classify by international reference standard such as ISO 1999:1990 standard [24].
Due to the impact of ethnic differences on the gene level, the associations can only be valid when they have been replicated in an independent population, therefore, this study was conducted for the first time on the Iranian population.
We did not detect that the genetic variability of GSTT1 and GSTM1 effect on susceptibility to noise induced hearing loss in Iranian population. Further studies should include workers with different noise exposure patterns. Combination of genes variation with other risk factors should also be analyzed.
(1). Noise-induced hearing loss is a complex disease affected by both genetic and environmental factors.
(2). Several Noise-induced hearing loss susceptibility genes has been suggested but oxidative stress genes are obvious candidate genes. One of important antioxidant enzymes in the cochlea are glutathione S-transferase (GST).
(3). This study investigates the association between GST gene polymorphism and noise induced hearing loss among Iranian noise-exposed workers.
(4). Further studies should include different population with different noise exposure patterns such as noise exposure levels, noise exposure times.
| [1] |
Yadav R, Pathak GS (2016) Intention to purchase organic food among young consumers: Evidences from a developing nation. Appetite 96: 122-128. doi: 10.1016/j.appet.2015.09.017
|
| [2] |
David W, Ardiansyah (2017) Organic agriculture in Indonesia: Challenges and opportunities. Org Agric 7: 329-338. doi: 10.1007/s13165-016-0160-8
|
| [3] | Devi LY, Anatasari E (2021) Key drivers of organic rice productivity in Sleman and Magelang Regencies Key drivers of organic rice productivity in Sleman and Magelang Regencies, 0-14. |
| [4] | AOI (2017) Statistik Pertanian Organik Indonesia 2016, Bogor. |
| [5] |
Rana J, Paul J (2017) Consumer behavior and purchase intention for organic food: A review and research agenda. J Retail Consum Serv 38: 157-165. doi: 10.1016/j.jretconser.2017.06.004
|
| [6] |
Scalco A, Noventa S, Sartori R, et al. (2017) Predicting organic food consumption: A meta-analytic structural equation model based on the theory of planned behavior. Appetite 112: 235-248. doi: 10.1016/j.appet.2017.02.007
|
| [7] |
Sultan P, Tarafder T, Pearson D, et al. (2020) Intention-behaviour gap and perceived behavioural control-behaviour gap in theory of planned behaviour: moderating roles of communication, satisfaction and trust in organic food consumption. Food Qual Prefer 81: 103838. doi: 10.1016/j.foodqual.2019.103838
|
| [8] | Chen MF, Tung PJ, Paul J, et al. (2016) Developing an extended Theory of Planned Behavior model to predict consumers' intention to visit green hotels. J Retail Consum Serv 27: 14-25. |
| [9] |
Carfora V, Cavallo C, Caso D, et al. (2019) Explaining consumer purchase behavior for organic milk: Including trust and green self-identity within the theory of planned behavior. Food Qual Prefer 76: 1-9. doi: 10.1016/j.foodqual.2019.03.006
|
| [10] |
Aertsens J, Verbeke W, Mondelaers K, et al. (2009) Personal determinants of organic food consumption: A review. Br Food J 111: 1140-1167. doi: 10.1108/00070700910992961
|
| [11] | Ajzen I (1991) The theory of planned behavior. Handb Theor Soc Psychol Vol 1 211: 438-459. |
| [12] |
Dorce LC, da Silva MC, Mauad JRC, et al. (2021) Extending the theory of planned behavior to understand consumer purchase behavior for organic vegetables in Brazil: The role of perceived health benefits, perceived sustainability benefits and perceived price. Food Qual Prefer 91: 104191. doi: 10.1016/j.foodqual.2021.104191
|
| [13] |
Ajzen I (2002) Residual Effects of Past on Later Behavior: Habituation and Reasoned Action Perspectives. Personal Soc Psychol Rev 6: 107-122. doi: 10.1207/S15327957PSPR0602_02
|
| [14] |
Bandura A (2007) Impeding ecological sustainability through selective moral disengagement. Int J Innov Sustain Dev 2: 8-35. doi: 10.1504/IJISD.2007.016056
|
| [15] | Isaskar R, Darwanto DH, Waluyati LR, et al. (2021) The Effects of Sensory Attributes of Food on Consumer Preference. J Asian Financ Econ Bus 8: 1303-1314. |
| [16] |
Chekima B, Chekima K, Chekima K (2019) Understanding factors underlying actual consumption of organic food: The moderating effect of future orientation. Food Qual Prefer 74: 49-58. doi: 10.1016/j.foodqual.2018.12.010
|
| [17] |
Boobalan K, Nachimuthu GS, Sivakumaran B (2021) Understanding the psychological benefits in organic consumerism: An empirical exploration. Food Qual Prefer 87: 104070. doi: 10.1016/j.foodqual.2020.104070
|
| [18] |
Lee HJ, Yun ZS (2015) Consumers' perceptions of organic food attributes and cognitive and affective attitudes as determinants of their purchase intentions toward organic food. Food Qual Prefer 39: 259-267. doi: 10.1016/j.foodqual.2014.06.002
|
| [19] |
Schouteten JJ, Gellynck X, Slabbinck H (2019) Influence of organic labels on consumer's flavor perception and emotional profiling: Comparison between a central location test and home-use-test. Food Res Int 116: 1000-1009. doi: 10.1016/j.foodres.2018.09.038
|
| [20] |
Kushwah S, Dhir A, Sagar M (2019) Understanding consumer resistance to the consumption of organic food. A study of ethical consumption, purchasing, and choice behaviour. Food Qual Prefer 77: 1-14. doi: 10.1016/j.foodqual.2019.04.003
|
| [21] |
Hartmann P, Ph D, Eisend M, et al. (2017) Warm glow vs. altruistic values : How important is intrinsic emotional reward in proenvironmental behavior? J Environ Psychol 52: 43-55. doi: 10.1016/j.jenvp.2017.05.006
|
| [22] |
Arsil P, Ardiansyah, Yanto T (2019) Consumers' Intention and Behaviour towards Fish Consumption: A Conceptual Framework. IOP Conf Ser Earth Environ Sci 255: 012006. doi: 10.1088/1755-1315/255/1/012006
|
| [23] | Septiani S, Najib M, Sumarwan U (2019) Egoistic and Altruistic Motives on the Purchasing Behavioral Model of Organic Food in the Indonesian market. 100: 40-45. |
| [24] | Irianto H (2015) Consumers' attitude and intention towards organic food purchase: An extension of theory of planned behavior in gender perspective. Int J Manag Econ Soc Sci 4: 17-31. |
| [25] |
Kusumaningsih D, Irianto H, Antriyandarti E (2019) Effects of health consciousness and environmental attitude on intention towards organic food purchase. IOP Conf Ser Mater Sci Eng 633: 012052. doi: 10.1088/1757-899X/633/1/012052
|
| [26] |
Vermeir I, Verbeke W (2008) Sustainable food consumption among young adults in Belgium: Theory of planned behaviour and the role of confidence and values. Ecol Econ 64: 542-553. doi: 10.1016/j.ecolecon.2007.03.007
|
| [27] |
Carrigan M, Attalla A, Carrigan M (2001) The myth of the ethical consumer ± do ethics matter in purchase behaviour? J Consum Mark 18: 560-578. doi: 10.1108/07363760110410263
|
| [28] |
Kö ster EP (2009) Diversity in the determinants of food choice: A psychological perspective. Food Qual Prefer 20: 70-82. doi: 10.1016/j.foodqual.2007.11.002
|
| [29] | Bagozzi RP (2008) The Self-Regulation of Attitudes, Intentions, and Behavior Author(s). Soc Psychol (Gott) 55: 178-204. |
| [30] |
Tarkiainen A, Sundqvist S (2005) Subjective norms, attitudes and intentions of Finnish consumers in buying organic food. Br Food J 107: 808-822. doi: 10.1108/00070700510629760
|
| [31] |
Chen M (2009) Attitude toward organic foods among Taiwanese as related to health consciousness, environmental attitudes, and the mediating effects of a healthy lifestyle. British Food J 111: 165-178. doi: 10.1108/00070700910931986
|
| [32] |
Asif M, Xuhui W, Nasiri A, et al. (2018) Determinant factors influencing organic food purchase intention and the moderating role of awareness: A comparative analysis. Food Qual Prefer 63: 144-150. doi: 10.1016/j.foodqual.2017.08.006
|
| [33] |
Johe MH, Bhullar N (2016) To buy or not to buy: The roles of self-identity, attitudes, perceived behavioral control and norms in organic consumerism. Ecol Econ 128: 99-105. doi: 10.1016/j.ecolecon.2016.02.019
|
| [34] |
Ajzen I, Fishbein M (1975) A Bayesian analysis of attribution processes. Psychol Bull 82: 261-277. doi: 10.1037/h0076477
|
| [35] |
Yazdanpanah M, Forouzani M (2015) Application of the Theory of Planned Behaviour to predict Iranian students' intention to purchase organic food. J Clean Prod 107: 342-352. doi: 10.1016/j.jclepro.2015.02.071
|
| [36] |
Bonne K, Vermeir I, Bergeaud-Blackler F, et al. (2007) Determinants of halal meat consumption in France. Br Food J 109: 367-386. doi: 10.1108/0070700710746786
|
| [37] |
Sadiq M, Paul J, Bharti K (2020) Dispositional traits and organic food consumption. J Clean Prod 266: 121961. doi: 10.1016/j.jclepro.2020.121961
|
| [38] | Magnusson MK, Arvola A, Hursti UK (2001) Attitudes towards organic foods among Swedish consumers. 103: 209-226. |
| [39] |
Chekima B, Igau A, Azizi S, et al. (2017) Narrowing the gap : Factors driving organic food consumption. J Clean Prod 166: 1438-1447. doi: 10.1016/j.jclepro.2017.08.086
|
| [40] | Steptoe A, Pollard TM, Wardle J (1995) Development of a Measure of the Motives Underlying the Selection of Food : the Food Choice Questionnaire. Appetite 267-284. |
| [41] |
Schleenbecker R, Hamm U (2013) Consumers' perception of organic product characteristics. A review. Appetite 71: 420-429. doi: 10.1016/j.appet.2013.08.020
|
| [42] | Cranfield JAL, Magnusson E (2003) Canadian Consumer's Willingness-To-Pay For Pesticide Free Food Products : An Ordered Probit Analysist1. Int Food Agribusiness Manage Rev 6: 13-30. |
| [43] |
Rozin P, Fischler C, Imada S, et al. (1999) Attitudes to food and the role of food in life in the U.S.A., Japan, Flemish Belgium and France: Possible implications for the diet-health debate. Appetite 33: 163-180. doi: 10.1006/appe.1999.0244
|
| [44] |
Gil MI, Tomas-Barberan FA, Hess-Pierce B, et al. (2000) Antioxidant activity of pomegranate juice and its relationship with phenolic composition and processing. J Agric Food Chem 48: 4581-4589. doi: 10.1021/jf000404a
|
| [45] |
Yadav R (2016) Altruistic or egoistic: Which value promotes organic food consumption among young consumers? A study in the context of a developing nation. J Retail Consum Serv 33: 92-97. doi: 10.1016/j.jretconser.2016.08.008
|
| [46] |
Von Essen E, Englander M (2013) Organic food as a healthy lifestyle: A phenomenological psychological analysis. Int J Qual Stud Health Well-being 8: 20559. doi: 10.3402/qhw.v8i0.20559
|
| [47] |
Grubor A, Djokic N (2016) Organic food consumer profile in the Republic of Serbia. Br Food J 118: 164-182. doi: 10.1108/BFJ-06-2015-0225
|
| [48] |
Krystallis A, Chryssohoidis G (2005) Consumers' willingness to pay for organic food: Factors that affect it and variation per organic product type. Br Food J 107: 320-343. doi: 10.1108/00070700510596901
|
| [49] |
Padel S, Foster C (2005) Exploring the gap between attitudes and behaviour: Understanding why consumers buy or do not buy organic food. Br Food J 107: 606-625. doi: 10.1108/00070700510611002
|
| [50] |
Smith S, Paladino A (2010) Eating clean and green? Investigating consumer motivations towards the purchase of organic food. Australas Mark J 18: 93-104. doi: 10.1016/j.ausmj.2010.01.001
|
| [51] |
Iweala S, Spiller A, Meyerding S (2019) Buy good, feel good? The influence of the warm glow of giving on the evaluation of food items with ethical claims in the U.K. and Germany. J Clean Prod 215: 315-328. doi: 10.1016/j.jclepro.2018.12.266
|
| [52] |
Schwartz SH (1973) Normative explanations of helping behavior: A critique, proposal, and empirical test. J Exp Soc Psychol 9: 349-364. doi: 10.1016/0022-1031(73)90071-1
|
| [53] |
Stern PC, Kalof L, Dietz T, et al. (1995) Values, Beliefs, and Proenvironmental Action: Attitude Formation Toward Emergent Attitude Objects. J Appl Soc Psychol 25: 1611-1636. doi: 10.1111/j.1559-1816.1995.tb02636.x
|
| [54] | Nurhayati A, Irham I (2020) Altruism Among Organic Rice Farmers in Yogyakarta. Agric Soc Econ J 20: 89-96. |
| [55] |
à YJ, Willems K, Brengman M, et al. (2010) Urban Forestry & Urban Greening The effects of urban retail greenery on consumer experience: Reviewing the evidence from a restorative perspective. Urban For Urban Green 9: 57-64. doi: 10.1016/j.ufug.2009.10.001
|
| [56] |
Andreoni J (1990) Impure Altruism and Donations to Public Goods: A Theory of Warm-Glow Giving. Econ J 100: 464-477. doi: 10.2307/2234133
|
| [57] |
Muntoro, Irham, Handoyo Mulyo J, et al. (2020) The existence of warm-glow motivation in indonesia organic farming. IOP Conf Ser Earth Environ Sci 518: 012043. doi: 10.1088/1755-1315/518/1/012043
|
| [58] |
Andrade C (2020) The Limitations of Online Surveys. Indian J Psychol Med 42: 575-576. doi: 10.1177/0253717620957496
|
| [59] |
Alzubaidi H, Slade EL, Dwivedi YK (2021) Examining antecedents of consumers' pro-environmental behaviours: TPB extended with materialism and innovativeness. J Bus Res 122: 685-699. doi: 10.1016/j.jbusres.2020.01.017
|
| [60] | Hair JF, Tomas GMH, Ringle CM, et al. (2014) A Primer on Partial Least Squares Structural Equation Modeling, United Kingdom, SAGE Publications, Inc. |
| [61] |
Reinartz W, Haenlein M, Henseler J (2009) An empirical comparison of the efficacy of covariance-based and variance-based SEM. Int J Res Mark 26: 332-344. doi: 10.1016/j.ijresmar.2009.08.001
|
| [62] |
Wang X, Pacho F, Liu J, et al. (2019) Factors influencing organic food purchase intention in Tanzania and Kenya and the moderating role of knowledge. Sustain 11: 209. doi: 10.3390/su11010209
|
| [63] |
Paul J, Modi A, Patel J (2016) Predicting green product consumption using theory of planned behavior and reasoned action. J Retail Consum Serv 29: 123-134. doi: 10.1016/j.jretconser.2015.11.006
|
| [64] | Voon JP, Sing K, Agrawal A (2011) Determinants of Willingness to Purchase Organic Food : An Exploratory Study Using Structural Equation Modeling. Int Food Agribusiness Manage Rev 14: 103-120. |
| [65] | Khoiriyah S, Juan M, Toro S, et al. (2013) The Antecedents of Attitude toward Green Product and Its Effect on Willingness to Pay and Intention to Purchase. International Conference on Business, Economics, and Social Sciences Proceeding, Bangkok, Indonesian Student Association in Thailand (PERMITHA), 17-20. |
| [66] | Bishop RC (2018) Warm Glow, Good Feelings, and Contingent Valuation. J Agric Resour Econ 43: 307-320. |
| [67] |
KotchenÃMJ (2005) Impure public goods and the comparative statics of environmentally friendly consumption. J Environ Econ Manage 49: 281-300. doi: 10.1016/j.jeem.2004.05.003
|
| [68] |
Hughner RS, McDonagh P, Prothero A, et al. (2007) Who are organic food consumers? A compilation and review of why people purchase organic food. J Consum Behav 6: 94-110. doi: 10.1002/cb.210
|
| [69] |
Hair JF, Ringle CM, Sarstedt M (2011) PLS-SEM: Indeed a silver bullet. J Mark Theory Pract 19: 139-152. doi: 10.2753/MTP1069-6679190202
|
| [70] | Chin WW (1998) The partial least squares approach for structural equation modeling. Mod methods Bus Res 295-336. |
| [71] |
Basha MB, Lal D (2019) Indian consumers' attitudes towards purchasing organically produced foods: An empirical study. J Clean Prod 215: 99-111. doi: 10.1016/j.jclepro.2018.12.098
|
| [72] | Hsu MS (2012) A study of internship attitude, subjective norm, perceived behavioral control, and career planning of hospitality vocational college students. J Hosp Leis Sport Tour Educ 11: 5-11. |
| [73] |
Hartmann P, Apaolaza-Ibáñez V (2012) Consumer attitude and purchase intention toward green energy brands: The roles of psychological benefits and environmental concern. J Bus Res 65: 1254-1263. doi: 10.1016/j.jbusres.2011.11.001
|
| [74] |
Ma C, Burton M (2016) Warm glow from green power: Evidence from Australian electricity consumers. J Environ Econ Manage 78: 106-120. doi: 10.1016/j.jeem.2016.03.003
|
| [75] |
Menges R, Schroeder C, Traub S (2005) Altruism, warm glow and the willingness-to-donate for green electricity: An artefactual field experiment. Environ Resour Econ 31: 431-458. doi: 10.1007/s10640-005-3365-y
|
| [76] |
Carrington MJ, Neville BA, Whitwell GJ (2010) Why ethical consumers don't walk their talk: Towards a framework for understanding the gap between the ethical purchase intentions and actual buying behaviour of ethically minded consumers. J Bus Ethics 97: 139-158. doi: 10.1007/s10551-010-0501-6
|
| [77] | Koklic MK, Golob U, Podnar K, et al. (2019) The interplay of past consumption, attitudes and personal norms in organic food buying. 137: 27-34. |
| [78] | Ouellette JA, Wood W (1998) Habit and Intention in Everyday Life: The Multiple Processes by Which Past Behavior Predicts Future Behavior. Am Psychol Assoc Inc 124: 54-74. |
| 1. | Xue-min Chen, Xin-miao Xue, Ning Yu, Wei-wei Guo, Shuo-long Yuan, Qing-qing Jiang, Shi-ming Yang, The Role of Genetic Variants in the Susceptibility of Noise-Induced Hearing Loss, 2022, 16, 1662-5102, 10.3389/fncel.2022.946206 | |
| 2. | Athena Rafieepour, Somayeh Farhang Dehgahn, Mahtab Firoozi, Rahim Gorji, Arash Ardalan, Mohammad Hossein Vaziri, Study Highlights Impact of Smoking on Hearing Loss Among Workers Exposed to Noise, 2022, 75, 0745-7472, 24,25,26, 10.1097/01.HJ.0000874576.86751.53 | |
| 3. | Fang Ji, Jian Zhang, Xiaowen Ding, Li Rong, Xiaodong Liu, Tenglong Yan, Jue Li, Associations of GST Gene Polymorphisms and GST Enzyme Activity with the Development of Noise-Induced Hearing Loss in Chinese Han Males, 2024, 27, 1662-4246, 168, 10.1159/000541618 | |
| 4. | Svyatoslav I. Mazilov, Nataliia E. Komleva, Tamara A. Novikova, Single nucleotide gene polymorphisms (SNPs) as markers of the increased risk of health disorders associated with exposure to industrial noise, 2023, 63, 2618-8945, 723, 10.31089/1026-9428-2023-63-11-723-729 | |
| 5. | Margaryta Amirkhanova, Julia Dieieva, THE EFFECT OF POLYMORPHISMS IN THE BCL2, BID AND BAX GENES ON THE DEVELOPMENT OF SENSORINEURAL HEARING LOSS, 2023, 25288253, 29, 10.37219/2528-8253-2023-3-29 |
Figures(2) / Tables(10)
Dhika Cahyasita, Irham, Jamhari. Intention to re-consume organic food: Sensory attributes, egoistic motive, and warm glow in the extended TPB[J]. AIMS Agriculture and Food, 2021, 6(4): 891-919. doi: 10.3934/agrfood.2021054
| Case group (n = 73) | Control group (n = 87) | P-Value | |
| Age (years)* (Mean±SD) | 35.12 ± 3.85 | 34.71 ± 4.21 | 0.07 |
| Employment (years)† (Mean±SD) | 6.40 ± 2.39 | 6.37 ± 1.72 | 0.90 |
| Noise exposure (TWA) dBA† (Mean±SD) | 90.14 ± 2.59 | 89.72 ± 2.32 | 0.26 |
| Smoking‡ 9N (%)] | 19 (26.00%) | 14 (16.10%) | 0.09 |
Note: *Student's
DownLoad:
CSV
| Genotypes | Case group n (%) | Control group n (%) | p-value | 0R (95% CI) |
| GSTT1 | ||||
| Normal genotype | 57 (78.1) | 70 (80.5) | 0.43 | 1.08 (0.72–1.61) |
| Null genotype | 16 (21.9) | 17 (19.5) | ||
| GSTM1 | ||||
| Normal genotype | 45 (61.6) | 61 (70.1) | 0.17 | 1.22 (0.87–1.71) |
| Null genotype | 28 (38.4) | 26 (29.9) | ||
DownLoad:
CSV
| Case group (n = 73) | Control group (n = 87) | P-Value | |
| Age (years)* (Mean±SD) | 35.12 ± 3.85 | 34.71 ± 4.21 | 0.07 |
| Employment (years)† (Mean±SD) | 6.40 ± 2.39 | 6.37 ± 1.72 | 0.90 |
| Noise exposure (TWA) dBA† (Mean±SD) | 90.14 ± 2.59 | 89.72 ± 2.32 | 0.26 |
| Smoking‡ 9N (%)] | 19 (26.00%) | 14 (16.10%) | 0.09 |
| Genotypes | Case group n (%) | Control group n (%) | p-value | 0R (95% CI) |
| GSTT1 | ||||
| Normal genotype | 57 (78.1) | 70 (80.5) | 0.43 | 1.08 (0.72–1.61) |
| Null genotype | 16 (21.9) | 17 (19.5) | ||
| GSTM1 | ||||
| Normal genotype | 45 (61.6) | 61 (70.1) | 0.17 | 1.22 (0.87–1.71) |
| Null genotype | 28 (38.4) | 26 (29.9) | ||
