Research article Special Issues

Testing consumer propensity towards novel optional quality terms: An explorative assessment of “mountain” labelled honey

  • The present study provides some preliminary reflections of the honey market and explores Italian consumer attitude towards the “mountain” quality term. Moreover, it also takes the organic and PDO labels into consideration, in addition to the generic “local” label, evaluating the relationships that exist between mountain honey and other products. Data were obtained through questionnaires using a face-to-face method and the econometric study was carried out using correlation analysis as a first step and then the one-way ANOVA and t-test, based on the socio-demographic and lifestyle characteristics; moreover, interactions among the characteristics mentioned above were evaluated using a two-way ANOVA with interaction. The results show that Italian consumers have a positive attitude towards “mountain” honey; however, their response changes according to the socio-demographic and lifestyle characteristics. An appreciable relationship was observed between mountain product and local product, suggesting that the mountain quality label could be a useful tool for the valorisation of honey.

    Citation: Filippo Brun, Raffaele Zanchini, Angela Mosso, Giuseppe Di Vita. Testing consumer propensity towards novel optional quality terms: An explorative assessment of “mountain” labelled honey[J]. AIMS Agriculture and Food, 2020, 5(2): 190-203. doi: 10.3934/agrfood.2020.2.190

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  • The present study provides some preliminary reflections of the honey market and explores Italian consumer attitude towards the “mountain” quality term. Moreover, it also takes the organic and PDO labels into consideration, in addition to the generic “local” label, evaluating the relationships that exist between mountain honey and other products. Data were obtained through questionnaires using a face-to-face method and the econometric study was carried out using correlation analysis as a first step and then the one-way ANOVA and t-test, based on the socio-demographic and lifestyle characteristics; moreover, interactions among the characteristics mentioned above were evaluated using a two-way ANOVA with interaction. The results show that Italian consumers have a positive attitude towards “mountain” honey; however, their response changes according to the socio-demographic and lifestyle characteristics. An appreciable relationship was observed between mountain product and local product, suggesting that the mountain quality label could be a useful tool for the valorisation of honey.


    Burnout is a common psychosocial phenomenon among health care workers. World Health Organization (WHO) defined Burn-out as an occupational phenomenon, “a syndrome conceptualized as resulting from chronic workplace stress that has not been successfully managed” [1]. It is composed of three dimensions: emotional exhaustion (EE), characterized by the sensation of physical and mental overexertion and lack of energy; (ii) depersonalization (DP) characterized by emotional detachment and negative attitudes towards patients and colleagues; and (iii) low personal accomplishment (PA), the degree to which a person perceives doing well on worthwhile tasks [2]. Burnout had negative effects on the employees, by causing different physical and mental problems and also on the organization, by decreasing the quality of care provided for patients and decreasing productivity [3]. A recent meta-analysis study that investigated burnout among nursing found a prevalence of 28% for high emotional exhaustion, 15% for high depersonalization and 31% for low personal accomplishment [4]. Burnout was associated with many sources of stress in the workplace such as work overload, long working hours, lack of resources and conflict with colleagues in addition to sociodemographic characteristics such as gender, age and years of experience. Previous studies in Saudi Arabia have been conducted among nurses in tertiary hospitals but not in the primary health care centers [5][8]. This study aimed to determine the prevalence and associated factors of burnout among nurses working in the primary health care centers in Medina city, Saudi Arabia.

    This observational analytical cross-sectional study was conducted among 200 nurses in the primary health care centers (PHC) in Medina city, Saudi Arabia. Al Madinah was divided into four regions, and three PHC centers were selected randomly from each region. All nurses in each center were approached. Those who had an experience of less than one-year were excluded.

    A self-administered questionnaire consisting of three parts was used in this study. The first part included questions on the sociodemographic characteristics. Level of education was categorized into two categories; Bachelor of Science Nursing (BSN; 4 years study and one-year internship) and Diploma in nursing (DN: three years study and 6 months internship).

    The second part assessed burnout by using the validated Maslach Burnout Inventory-Human Services Survey (MBI-HSS) which is the most commonly used tool for assessing burnout. It consists of 22 items which are divided into three subscales: emotional exhaustion, 9 items (the feelings of being emotionally overrun and exhausted by one's work); depersonalization, 5 items (the tendency to view others as objects rather than as feeling persons) and personal accomplishment, 8 items (the degree to which a person perceives doing well on worthwhile tasks). The items are answered in a 7-point scale ranging from 0 (never) to 6 (every day) [2]. The three scores are calculated for each respondent. High scores for EE and DP indicated higher levels of burnout, while high scores for PA indicated lower levels of burnout. This instrument was validated in many languages including Arabic language [9]. Cronbach's alpha coefficient for the three MBI subscales of the Arabic version were: emotional exhaustion (alpha = 0.88), depersonalization (alpha = 0.78), personal accomplishment (alpha = 0.89) [9] High level of burnout is defined in this study as high score on any of the three subscales of burnout [9],[10]. Sources of stress were assessed by 10 items which were obtained from the literature [10]. These items were headed by the following question: “to which extent dose the following conditions cause stress to you”. Each item was scored from zero (causing no stress) to 4 (causing severe stress) [10].

    Ethical approval was obtained from the Ethics Committee of the Directorate of Health in Al-Madinah. Objectives and benefits of the study were explained to the participants. Participants confidentiality and anonymity were assured. Signed consents were obtained from the participants.

    Analysis was performed using Statistical Package for the Social Sciences (SPSS®) (version 22.0, IBM, Armonk, NY). The 22 items of MBI were summed to obtain the total score of each subscale [2].

    Each subscale was categorized into low, moderate and high according to the recommended cut-off points [9]. Test of normality was performed for each subscale. T-test and analysis of variance (ANOVA) test were used to assess the association between burnout subscales and the sociodemographic variables. Pearson Correlation coefficient was used to assess the association between burnout subscales and the sources of stress. To obtain the significant factors associated with each subscale of burnout, multiple linear regression analysis was employed by using “Backward” technique. Multi-collinearity was checked between the independent variables by using the VIF. The accepted level of significance was below 0.05 (p < 0.05).

    Most participants were females (73.0%), aged ≤35 years (52.0%), married (81.0%) and had >10 years of service. Most of them had no administrative work (80.0%), had diploma (75.0%) and had a monthly income of less than 12 thousand Saudi Rial (SAR) (53.0%) (Table 1).

    Table 1.  Socio-demographic characteristics of the participants.
    n %
    Age
     ≤35 104 52.0
     >35 96 48.0
    Gender
     Male 54 27.0
     Female 146 73.0
    Marital status
     Single 30 15.0
     Married 162 81.0
     Divorced/widower 8 4.0
    Educational level
     Diploma 150 75.0
     Bachelor 50 25.0
    Years of service
     5 or less 32 16.0
     6–10 57 28.5
     >10 111 55.5
    Administrative task
     Yes 40 20.0
     No 160 80.0
    Monthly income (SAR)*
     <12000 106 53.0
     ≥12000 94 47.0

    Note: *1 USD = 3.7 SAR.

     | Show Table
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    About 39% had high EE, 38% had high DP and 85.5% had low PA. Forty-five participants (22.5%) scored high on all the three subscale of burnout and 178 scored high at least on one subscale of burnout (89%) (Table 2). The reliability analysis of the three subscales yielded Cronbach alpha of 0.84 for EE, 0.76 for DP and 0.85 for PA.

    Table 2.  Prevalence of burnout among participants.
    Low n (%) Moderate n (%) High n (%)
    EE 72 (36) 50 (25) 78 (39)
    DP 46 (23) 78 (39) 76 (38)
    PA 171 (85.5) 11 (5.5) 18 (9.0)

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    The most important sources of stress were long working hours, work overload, fear of violence and lack of resources (Table 3).

    Table 3.  Sources of stress in the workplace ranked by mean.
    Item Mean
    Long working hours 3.161
    Work overload 2.779
    Fear of violence 2.623
    Lack of resources 2.588
    Work demands affect my personal homelife 2.362
    Fear of making mistake that can lead to serious consequences 2.302
    Working with uncooperative colleagues 2.302
    Poor work environment 2.281
    Office work 1.985
    Cannot participate in decision-making 1.995

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    Table 4.  Relationship between burnout and socio-demographic characteristics.
    Variables Nurses' burnout
    EE
    DP
    PA
    Mean (SD) P value Mean (SD) P value Mean (SD) P value
    Age
     ≤35 21.4 (11.5) 8.9 (5.0) 21.2(5.8)
     >35 24.9 (13.5) 0.041 9.6 (6.4) 0.348 16.1(5.5) 0.002
    Gender
     Male 23.4 (13.4) 9.2 (5.2) 17.9 (6.2)
     Female 22.9 (12.2) 0.807 9.3 (5.1) 0.855 19.0 (5.0) 0.502
    Marital status
     Single 22.2 (13.1) 8.9 (5.2) 20.0(5.4)
     Married 23.2 (12.5) 9.3 (5.7) 18.3(5.1)
     Divorced/widower 22.6 (13.8) 0.910 9.3 (7.2) 0.926 17.7(6.2) 0.794
    Educational level
     Diploma 21.2 (12.8) 9.2 (5.8) 20.8 (5.4)
     University 28.4 (10.3) <0.001 9.4 (5.5) 0.800 14.2 (7.2) 0.001
    Years of service
     5 or less 22.8 (12.1) 8.3 (4.5) 22.8 (4.2)
     6–10 21.9 (11.3) 9.4 (5.3) 19.4 (6.4)
     >10 23.7 (13.3) 0.658 9.4 (6.2) 0.627 17.3 (5.7) 0.060
    Administrative task
     Yes 22.4 (11.2) 8.7 (5.4) 23.2 (6.5)
     No 23.2 (12.9) 0.727 9.4 (5.8) 0.464 17.7 (7.4) 0.021
    Monthly income (SAR)
     <12000 24.6 (11.8) 10.5 (5.5) 26.3 (6.4)
     ≥12000 22.0 (12.9) 0.138 8.4 (5.7) 0.014 25.5 (5.6) 0.921

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    In univariate analysis, emotional exhaustion score was significantly higher among those aged >35 years (24.9 ± 13.5) compared to those aged ≤35 years (21.4 ± 11.5), (p = 0.041), and among those who had Bachelor degree (28.4 ± 10.3) compared to those who had diploma (21.2 ± 12.8), (p < 0.001) (Table 4).

    EE was correlated positively and significantly with all the ten sources of stress (r coefficient ranged from 0.379 to 0.586), (p < 0.001) (Table 5). DP was higher among those who had an income of <12000 SAR (10.5 ± 5.5) compared to those with income of ≥12000 (8.4 ± 3.7), (p = 0.014) (Table 4). DP was correlated positively and significantly with all the ten sources of stress (r coefficient ranged from 0.198 to 0.368), (p < 0.005) (Table 5). PA was significantly lower among those who aged >35 years (16.1 ± 5.5) compared to those aged ≤35 years (21.2 ± 5.8), (p = 0.002), among those who had university degree (14.2 ± 7.2) compared to those who had diploma (20.8 ± 5.4), (p = 0.001) and among those who had not administrative task (17.7 ± 7.4) compared to those who had (23.2 ± 6.5), (p = 0.021) (Table 4).

    Table 5.  Relationship between burnout and sources of stress in the workplace.
    Item EE
    DP
    PA
    Coefficient P value Coefficient P value Coefficient P value
    Work overload 0.495 <0.001 0.204 0.004 −0.106 0.135
    Long working hours 0.379 <0.001 0.198 0.005 −0.007. 0.926
    Fear of violence 0.422 <0.001 0.216 0.002 −0.100 0.161
    Poor work environment 0.586 <0.001 0.368 <0.001 −0.219 0.002
    Lack of resources 0.511 <0.001 0.301 <0.001 −0.086 0.228
    Fear of making mistake that can lead to serious consequences 0.428 <0.001 0.220 <0.001 −0.097 0.174
    Working with uncooperative colleagues 0.362 <0.001 0.197 0.005 −0.064 0.365
    Office work 0.340 <0.001 0.273 <0.001 −0.055 0.436
    Cannot participate in decision-making 0.424 <0.001 0.329 <0.001 −0.028 0.697
    Work demands affect my personal home life 0.525 <0.001 0.249 <0.001 −0.0091 0.200

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    In multivariate analysis, significant predictors of EE were work overload (p = 0.010), poor work environment (p < 0.001), lack of resources (p = 0.033), working with uncooperative colleagues (p = 0.005), work demands affect personal homelife (p < 0.001) and having university education (p < 0.001) (Table 6). Significant predictors of DP were poor work environment (p < 0.001), “cannot participate in decision-making” (p = 0.041) and low income (<12000 SAR) (Table 6). Low personal accomplishment was significantly predicted by age (>35 years) (p=0.001), educational level (university), (p = 0.004) and no administrative task (p = 0.003) (Table 6).

    Table 6.  Factors associated with burnout in multivariate analysis.
    B SE Beta P value VIF
    Emotional exhaustion
    Work overload 1.636 0.63 0.170 0.010 1.688
    Poor work environment 3.134 0.68 0.318 <0.001 1.887
    Lack of resources 1.473 0.68 0.148 0.033 1.853
    Fear of making mistake that can lead to serious consequences 1.038 0.59 0.110 0.082 1.565
    Working with uncooperative colleagues 1.875 0.65 −0.199 0.005 1.907
    Work demands affect my personal home life 2.226 0.56 0.267 <0.001 1.774
    University (reference = diploma) 6.009 1.51 0.206 <0.001 1.052
    Depersonalization
    Poor work environment 1.246 0.35 0.278 <0.001 1.246
    Cannot participate in decision-making 0.702 0.35 0.156 0.041 0.702
    Monthly income less than 12K SAR −1.776 0.76 −0.0152 0.021 −1.776
    Personal accomplishment
    Age (>35) −5.550 1.59 −0.0234 0.001 1.009
    Educational level (Bachelor) −5.354 1.82 −0.0196 0.004 1.001
    No administrative task −5.960 1.98 −0.0201 0.003 1.010

     | Show Table
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    The primary aim of this study was to estimate the prevalence of burnout and its associated factors among nurses in the primary health care setting. This study found 89% of the participants scored high at least on one subscale of burnout. Low personal accomplishment was found among 89% of nurses while high EE and high DP were reported by 39%, and 38% respectively. Moderate level of burnout was found among 25% (EE), 39% (DP) and 5.5% (PA). The overall prevalence of burnout in this study was 89%.

    Previous studies among nurses in Saudi Arabia found that 32 % to 71.6% of nurses had high levels of burnout [5][8]. It was found by Al-Turki et al. that 45% of nurses had high EE, 42% had high depersonalization and 71.5% had low personal accomplishment. [5] Another study from Saudi Arabia found that 71.6 % of nurses had high level of burnout. [7] Another study from Saudi Arabia reported that 42% of nurses had moderate level of stress. [8] However, these two previous studies did not define the cut-off point for burnout. All the other mentioned studies used Maslach burnout inventory.

    A recent study from Egypt found that 54.6% of nurses had average levels of emotional exhaustion, 48% scored high on depersonalization, and 77.5% had low personal accomplishment [11]. Another study from Egypt found that 52.8% of nurses experienced high EE, 7.2% had high level of DP and 96.5% had low PA [12]. A study among Iranian nurses found that 25% of the participants had high level of burnout. [13] A study of nurses in Israel reported that 30.8% reported high emotional exhaustion, 5.1% had high depersonalization, and 84.6% had low personal accomplishment [14]. In Jordan 55% of nurses reported high level of emotional exhaustion, 50% reported high level of depersonalization, and 50% reported low personal accomplishment [15]. A recent international meta-analysis study that investigated burnout among nurses found that 28% of nurses had high level emotional exhaustion, 15% had high level of depersonalization and 31% had low personal accomplishment [4]. Regarding factors associated with burnout, this study found that high emotional exhaustion was associated with age group, level of education, and with sources of stress in the work place such as work overload, lack of resources, uncooperative colleagues, and poor working environment. DP was associated with low income, poor working environment and inability to participate in decision-making. Low PA was associated with age group, level of education and no engagement in administrative work.

    While some studies had not found association between burnout and socio-demographic factors, [8] some other studies had found a significant association between burnout and age, marital status and education level [5],[7]. However, there is a great agreement between studies that burnout is associated with stress and sources of stress in the workplace [15][20].

    That sources of stress in the workplace included role conflict, work overload, conflict with colleagues, long working hours, poor working environment and low supervisor support. A previous meta-analysis study found that job insecurity, low job control, low reward, high demands and high work load increased the risk for developing burnout [21].

    Long-term exposure to stressors was found to affect the professional quality of life, leading to cognitive and emotional distress and burnout [22]. Continuous effort in stressful, demanding tasks can have physiological and psychological impacts, such as increased heart rate and prolonged stimulation of the sympathetic nervous system. This is well recognized to be associated with exhaustion, particularly when the workload is high. Long working hours was found to be associated with emotional exhaustion because it produces excessive demands and disrupt family life and ability to trail outside interests [15][17].

    This finding emphasis that any effort to manage burnout should be directed toward the management of sources of stress in the work place. Burnout was also found to be affected by other factors rather than work related factors and stressors in the work place. It was found in the previous studies that Alexithymic personality trait increased likelihood to experience burnout and has a negative effect on the professional quality of life among. radiation oncologists [23],[24]. In addition, emotional intelligence was found to be linked with all the three parts of burnout [25]. Emotional intelligence is defined as the ability to perceive emotion, integrate emotion to facilitate thought, understand emotions, and regulate emotions to promote personal growth [26].

    This study found that 89% of the participants scored high at least on one subscale of burnout. Burnout was associated mainly with work related sources of stress. A comprehensive interventional approach is needed to minimize and prevent burnout among nurses in the primary health care centers. There were three types of interventions to manage burnout: individual-focused, organizational, and combine interventions. Individual-focused interventions included self-care workshops, stress management skills, communication skills training, yoga, mindfulness, meditation and coping programs. Organizational interventions aimed mainly to reduces stress and to mitigate the impact of stressors in the workplace; they included workload or schedule-rotation, stress management training program, access to peer mentoring, help and guidance from experienced work colleagues and teamwork/transitions. Individual and organizational interventions should be combined to effectively reduce burnout among healthcare providers. It would be also of great interest if future studies investigate which personality factors are associated with burnout in nursing working in primary health care centers. This will help to prioritize intervention to focus on nurses with high risk personality trait. Interventions to improve emotional intelligence are also recommended. Poulsen & Poulsen (2018) proposed a Self-Determination Theory and they suggested two steps to prevent burnout during early career. The first step was to educate trainers and trainees about times when individuals may be vulnerable to work stress. Learning how to recognize the warning signs of burnout and being aware of vulnerability is a vital first step. Education about the need for self-awareness and importance of self-care would occur in the early stages of training. The next step involved alerting practitioners regarding the extent and accessibility of information regarding evidence-based strategies that can be employed to address exhaustion and prevent disengagement [27].



    [1] Finco A, Bentivoglio D, Bucci G (2017) A label for mountain products? Let's turn it over to producers and retailers. Qual Success 18: 198-205.
    [2] Bentivoglio D, Savini S, Finco A, et al. (2019) Quality and origin of mountain food products: the new European label as a strategy for sustainable development. J Mt Sci 16: 428-440. doi: 10.1007/s11629-018-4962-x
    [3] Arvanitoyannis I, Krystallis A (2006) An empirical examination of the determinants of honey consumption in Romania. Int J Food Sci Technol 41: 1164-1176. doi: 10.1111/j.1365-2621.2006.01174.x
    [4] Jsenen JD, Mørkbak MR (2013) Role of gastronomic, externality and feasibility attributes in consumer demand for organic and local foods: The case of honey and apples. Int J Consum Stud 37: 634-641. doi: 10.1111/ijcs.12049
    [5] Blanc S, Brun F, Di Vita G, et al. (2018) Traditional beekeeping in rural areas: profitability analysis and feasibility of pollination service. Qual Success 19: 72-79.
    [6] Batt PJ, Liu A (2012) Consumer behaviour towards honey products in Western Australia. Br Food J 114: 285-297. doi: 10.1108/00070701211202449
    [7] Wu S, Fooks JR, Messer KD, et al. (2015) Consumer demand for local honey. Appl Econ 47: 4377-4394. doi: 10.1080/00036846.2015.1030564
    [8] Pippinato L, Di Vita G, Brun F (2019) Trade and comparative advantage analysis of the EU honey sector with a focus on the Italian market. Qual Success 20: 485-492.
    [9] Blanc S, Brun F, Mosso A, et al. (2019) An overview of the international beekeeping sector (in Italian), In: University of Turin, An overview of the structure, production and trade of honey (in Italian), Turin, 27-42.
    [10] Italian Law No 97 of 31 January 1994 "New provisions for mountain areas" (in Italian). Official gazette of the Italian Republic, general series n.32.
    [11] EU (2012) Regulation No 1151/2012 of the European Parliament and of the Council of 21 November 2012 on quality schemes for agricultural products and foodstuffs. Official Journal of the European Union, L 343/1.
    [12] EC (1999) Council Regulation No 1257/1999 of 17 May 1999 on support for rural development from the European Agricultural Guidance and Guarantee Fund (EAGGF) and amending and repealing certain Regulations. Official Journal of the European Communities, L 160/80.
    [13] EU (2014) Commission Delegated Regulation No 665/2014 of 11 March 2014 supplementing Regulation (EU) No 1151/2012 of the European Parliament and of the Council with regard to conditions of use of the optional quality term "mountain product". Official Journal of the European Union, L 179/23.
    [14] Decree of 26 July 2017 National provisions for the implementation of Regulation (EU) No 1151/2012 and Delegated Regulation (EU) No 665/2014 on the conditions of use of the optional quality term "mountain product" (in Italian). Official Gazette of the Italian Republic, general series n.214.
    [15] Decree of 2 August 2018. Establishment of the identification logo for the optional quality indication 'mountain product' in implementation of Ministerial Decree No 57167 of 26 July 2017 (in Italian)., Official Gazette of the Italian Republic, general series n.227.
    [16] MIPAAF (2019) List of products with optional quality indication "mountain product" (in Italian). Available from: https://www.politicheagricole.it/flex/cm/pages/ServeBLOB.php/L/IT/IDPagina/11687.
    [17] Brosdahl DJ, Carpenter JM (2011) Shopping orientations of US males: A generational cohort comparison. J Retail Consum 18: 548-554. doi: 10.1016/j.jretconser.2011.07.005
    [18] Kowalczuk I, Jeżewska-Zychowicz M, Trafiałek J (2017) Conditions of honey consumption in selected regions of Poland. Acta Sci Pol Technol Aliment 16: 101-112.
    [19] Scarpa R, Del Giudice T (2004) Market segmentation via mixed logit: extra-virgin olive oil in urban Italy. J Agric Food Ind Organ 2: 141-160.
    [20] Verbeke W, Pieniak Z, Guerrero L, et al. (2012) Consumers' awareness and attitudinal determinants of European Union quality label use on traditional foods. Bio-based Appl Econ J 1: 213-229.
    [21] Brščić K, Šugar T, Poljuha D (2017) An empirical examination of consumer preferences for honey in Croatia. Appl Econ 49: 5877-5889. doi: 10.1080/00036846.2017.1352079
    [22] Capitello R, Agnoli L, Begalli D (2016) Drivers of high-involvement consumers' intention to buy PDO wines: Valpolicella PDO case study. J Sci Food Agric 96: 3407-3417. doi: 10.1002/jsfa.7521
    [23] Ismaiel S, Kahtani S, Adgaba S, et al. (2014) Factors That Affect Con-sumption Patterns and Market Demands for Honey in the Kingdom of Saudi Arabia. Food Nutr Sci 5: 1725-1737.
    [24] Sanlier N, Sezgin A, Sahin G, et al. (2018) A study about the young consumers' consumption behaviors of street foods. Cien Saude Colet 23: 1647-1656. doi: 10.1590/1413-81232018235.17392016
    [25] Vu TMH, Tu VP, Duerrschmid K (2016) Design factors influence consumers' gazing behaviour and decision time in an eye-tracking test: A study on food images. Food Qual Prefer 47: 130-138. doi: 10.1016/j.foodqual.2015.05.008
    [26] Jin SV, Phua J (2016) Making reservations online: The impact of consumer-written and system-aggregated User-Generated Content (UGC) in travel booking websites on consumers' behavioral intentions. J Travel Tour Mark 33: 101-117. doi: 10.1080/10548408.2015.1038419
    [27] Rouder JN, Engelhardt CR, McCabe S, et al. (2016) Model comparison in ANOVA. Psychon Bull Rev 23: 1779-1786. doi: 10.3758/s13423-016-1026-5
    [28] Fox J, Bouchet-Valat M (2019) Rcmdr: R Commander. R package version 2.5-2.
    [29] Cosmina M, Gallenti G, Marangon F, et al. (2016) Reprint of "Attitudes towards honey among Italian consumers: A choice experiment approach". Appetite 106: 110-116. doi: 10.1016/j.appet.2016.08.005
    [30] Di Vita G, Caracciolo F, Brun F, et al. (2019) Picking out a wine: Consumer motivation behind different quality wines choice. Wine Econ Policy 8: 16-27. doi: 10.1016/j.wep.2019.02.002
    [31] Feldmann C, Hamm U (2015) Consumers' perceptions and preferences for local food: A review. Food Qual Prefer 40: 152-164. doi: 10.1016/j.foodqual.2014.09.014
    [32] Schjøll A, Amilien V, Arne Tufte P, et al. (2010) Promotion of mountain food: An explorative a study about consumers' and retailers' perception in six European countries, 9th European IFSA Symposium, 1558-1567.
    [33] Bryła P (2017) The perception of EU quality signs for origin and organic food products among Polish consumers. Qual Assur Saf Crop Foods 9: 345-355. doi: 10.3920/QAS2016.1038
    [34] Menozzi D, Halawany-Darson R, Mora C, et al. (2015) Motives towards traceable food choice: A comparison between French and Italian consumers. Food Control 49: 40-48. doi: 10.1016/j.foodcont.2013.09.006
    [35] Annunziata A, Pomarici E, Vecchio R, et al. (2016) Do consumers want more nutritional and health information on wine labels? Insights from the EU and USA. Nutrients 8: 416.
    [36] Di Vita G, Pappalardo G, Chinnici G, et al. (2019) Not everything has been still explored: Further thoughts on additional price for the organic wine. J Clean Prod 231: 520-528. doi: 10.1016/j.jclepro.2019.05.268
    [37] Pelletier JE, Laska MN, Neumark-Sztainer D, et al. (2013) Positive attitudes toward organic, local, and sustainable foods are associated with higher dietary quality among young adults. J Acad Nutr Diet 113: 127-132. doi: 10.1016/j.jand.2012.08.021
    [38] 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.
    [39] Illichmann R, Abdulai A (2013) Analysis of consumer preferences and willingness-to-pay for organic food products in Germany, Agricultural & Applied Economics Association's 2013 AAEA & CAES Joint Annual Meeting, Washington, DC, 24.
    [40] Cholette S, Ungson GR, Özlük Ö, et al. (2013) Exploring purchasing preferences: Local and ecologically labelled foods. J Consum Mark 30: 563-572. doi: 10.1108/JCM-04-2013-0544
    [41] Hempel C, Hamm U (2016) How important is local food to organic-minded consumers? Appetite 96: 309-318. doi: 10.1016/j.appet.2015.09.036
    [42] Di Vita G, Blanc S, Brun F, et al. (2019) Quality attributes and harmful components of cured meats: Exploring the attitudes of Italian consumers towards healthier cooked ham. Meat Sci 155: 8-15. doi: 10.1016/j.meatsci.2019.04.013
    [43] Roy S, Guha A, Biswas A (2015) Celebrity endorsements and women consumers in India: how generation-cohort affiliation and celebrity-product congruency moderate the benefits of chronological age congruency. Mark Lett 26: 363-376. doi: 10.1007/s11002-015-9354-1
    [44] Pappalardo G, Di Vita G, Zanchini R, et al. (2019) Do consumers care about antioxidants in wine? The role of naturally resveratrol-enhanced wines in potential health-conscious drinkers' preferences. Br Food J: ahead-of-print.
    [45] Bentivoglio D, Bucci G, Finco A (2019) Farmers' general image and attitudes to traditional mountain food labelled: a swot analysis. Calitatea 20: 48-55.
    [46] McMorran R, Santini F, Guri F, et al. (2015) A mountain food label for Europe?. The role of food labelling and certification in delivering sustainable development in European mountain regions. J Alp Res Rev géographie Alp 103: 1-22.
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