The psychological perspective on the adoption of approved genetically modified crops in the presence of acceptability constraint: the contingent role of passion

ABSTRACT

This study contributes to the literature on genetically modified crops by examining the impact of psychological distance on farmer adoption. The existing body of literature suggests that some farmers have the conservative perception to adopt genetically modified crops because of controversies regarding the side effects and profitability. To understand these social problems, we have relied upon construal-level theory which argues farmer passion about dynamics like here and now, likely or unlikely and the near or far from self are vital for the adoption of approved genetically modified crops. The data for the present study collected from three Asian countries through questionnaire, for China 300, India 350, Philippines 300 valid responses collected. The study founds a positive relation of psychological distance based on passion with farmer trust behavior to adopt genetically modified crops over time. The findings of the present study provide new insights into the development of farmer acceptability and encourage the use of novel crop technologies.

Abbreviations: GM, genetically modified; TD, temporal distance; SPD, Spatial distance; SD, Social distance; TB, trust behavior; AGMC, Approved Genetically modified crops; CLT, Construal Level Theory

1. Introduction

Genetically Modified (GM) crops, first commercially introduced in the 1990s,¹and their adoption originates many socio-economic and sustainability opportunities for farmers. GM food also provides numerous health benefits for consumers around the globe.² Recent advancements in crops technological have played a vital role in multiplying the productivity of agricultural products.³ In 2017 across the globe, 77% of soybean, 80% of cotton, 32% of maize, and 30% of canola were modified varieties of these crops.⁴

Recently GM crops experience positive adoption intentions from farmers. The overall cultivation of GM crops was around 189.8 million hectares at the end of 2017. At the end of 2017, there were 67 countries, including 19 developing and five industrial countries, using GM crops. Moreover, another 43 countries have introduced formal measures for the use of biotech crops. From 1996–2017, 15.4 million farmers cultivated 148 million hectares of GM crops in approximately 29 countries; 90% of these farmers fell under the category of small-scale resource-poor farmers of developing countries^I Some countries have an unmatched wealth of resource-poor farmers who can provide critical information and insight toward a better understanding of the socio-economic situation for approved GM crops. According to⁴ farmers are not well aware of biotech crops and have a reservation to cultivate the approved GM crops; due to reliance on traditional seeds and practices. GM policymaker and scholars are very active in the dissemination of useful knowledge to promote GM crops and consider it a measure to fight against hunger and food shortages. On one hand, prior literature exhibits existence of trust deficit between policymakers, scientists, and farmers regarding the GM crops and allied adoption^5,6 because of unknown health risks and a severe biological threat inherited in GM crops.⁷ Another concern is that transgenic crop patents and intellectual property rights may result in market capture and rise of monopolies.⁸ Eventually, the success of GM crops will depend on governmental approval and farmer trust. Therefore, trust in public and private organizations is the primary factor in determining the economic prospect for the approved GM crops.

On the other hand, a general census exists on central role of trust in establishing and maintaining close, cooperative, and productive relationships among GM stakeholders.^9–12 In this context, the study focus on the cognitive aspect of trustworthiness, i.e. a behavioral intention of the farmer to trust approved GM crops. Farmer vested trust in individual and institutions has a beneficial impact on user behavioral intentions.¹³ Farmer behavioral intention is the most favorable predictor of actual cultivation of approved GM crops to enhance agricultural productivity.^14,15 Generally, farmers hold a positive attitude toward the benefit of GM crops¹⁶ and indicate the possible success of novel crop technologies.^17,18 We contend that it is imperative to develop a construal-level approach that helps to achieve a farmer trust to adopt the approved GM crops.

Present paper address the research question by hypothesizing dimensions of psychological distance: temporal, spatial, and social distance mediated by trust and moderated by the role of passion. Farmer trust behavior with the integration of psychological distance has a substantial impact on the adoption of approved GM crops. Prior research suggests that there were different acceptability levels of GM crops across different countries, and this acceptability highly influenced by the knowledge of GM technology and trust.¹⁹ For instance, Eurozone have reservations and depicts less supportive intentions for GM crops,²⁰ compared to the United States,²¹ Japan,²² South Africa,²³ and China.²⁴ Regulatory authorities in Europe have significantly lower trust in comparison to the United States^25,21 However, the story in the China, India, and Philippines is different for GM crops and food; there is limited research on the adoption of approved GM crops and the impact of psychological distance on farmer intentions.

This study intends to make three significant contributions. First, the study goes beyond the extant research, which primarily develops the theoretical approach to link individual cognition based on passion and trust behavior with the adoption of approved GM crops at an individual level in a dynamic environment. “Individual cognition” is the mental process of intellectual functions such as acquiring knowledge, evolution, computation, decision-making, problem solving and understanding of surrounding by direct and indirect experience.²⁶ It enables the farmers to use the conventional way to cultivate the novel crops according to the country rules and regulations.

Second, psychological distance is directly observed to attain higher acceptance for the approved GM crops and less for traditional crops, which can serve as a foundation for individual cognition understanding along with other, less directly observed, dimensions. We utilize the concept of construal refers to personal knowledge, interpretations, evaluation, and understanding about the environment – as a theoretical approach that supports us to make the association of psychological distance to the farmer cognition. Thus, we advance the field of GM crops and food practice and open the door for future research by showing the implicit and explicit connection between farmer cognition and novel biotechnology. We also have developed a dynamic mechanism through individual passion which influences the farmer cognition in alternative space, time contrasts, and social distance. Individual passion is a strong positive feeling which motivates the farmers to involve in the business activities in the context of cultivating the GM crops that provide substantial support to the food-related industries.

The third contribution is comparative between developed and developing countries. GM crops and food is an entirely new phenomenon and it may spread from developed nations to those that are developing or under-developing. The exploration and exploitation of novel biotechnology may path dependent and currently better well-known in developed countries.²⁷ While the demand for GM crops and food may be more substantial in developing and under-developing countries. In under develop countries, farmers mostly struggle to satisfy their fundamental requirements such as living incomes, while in more advanced nations people seek opportunities to meet higher-order requirements.

2. Developing Trends and Background

2.1. Global Area of Biotech: Specifically China, India, and Philippine

In 2017 total GM cultivation was around 190 million hectares, a 3% increase compared to 2016.⁴ The stats show USA, Brazil, Argentina, and Canada have the top cultivators of GM crops to date.⁴ Whereas the current study focuses on developing countries, India is the fifth to adopt and cultivate crops, almost 11.4 million hectares followed by China and Philippines with 2.8 million and 0.6 million hectares. This statistical information does not represent the village level non-registered adoption of approved GM crops. Moreover, in these three countries, individual states have shown the fast adopter trend of GM crops in some villages and many other villages lacks to follow a similar passion (see Table 1).^II

Table 1.

Cultivated Area of novel Crops.

Countries (1996 to 2017)	Area (Million Hectares)
1. India	11.4
2. Pakistan	3.0
3. China	2.8
4. Philippines	0.6
5. Myanmar	0.3

adopted from⁴

2.1.1. India

The commercialization of GM crops kicks off with Bt cotton in 2002,²⁸ and small landholders were targeted with specific incentives to experience and evaluate the GM crop. Later in 2017, overall GM crop cultivating land raised to 6 lac hectares of Bt cotton from 10.8 million hectares in 2016 to 11 million hectares, equivalent to 93% of the total cotton area cultivated 12.24 million hectares in the country.⁴ Farmer approval rate increased rapidly due to financial benefits associated with GM variety. However, other popular GM crops such as Bt brinjal, GM mustard in the field test and yet not approved for commercial plantation (GEAC) (See Table 2)^II.

Table 2.

Approved commercial/non-commercial/trail GM crops in India

year	GM crops	Approved types	Area (million hectares)	Status
2002	Cotton	Gossypium hirsutum L BNLA-601	~10.8 million hectares	Commercially approved: Genetic Engineering Approval Committee (GEAC) approved this product for farmers to cultivation. Within the country farmer can also adopt and sell this product without any legal constraints
2007	Brinjal	Bt Brinjal	Unknown	In 2007 GEAC approved for commercial use but in 2010 Environmental minister Jairam Ramesh blocked that initiative because of less lack of consensus among scientists and opposition
1998	GM-mustard	DMH-11	Unknown	Trail: GEAC approved this product for trail to check the productivity, quality and health measures. This product is not available for farmers to cultivation.

Source: India Biosafety Clearing House, USDA-FAS GAIN Report – India, GEAC Biosafety Data of Approved GM crops.

2.1.2. China

China has been one of the leaders of GM cotton cultivation along with considerable plantation of biotech papaya and GM poplar trees.²⁹ Roughly 6 to 7 million farmers benefitted from GM crops due to high return with cost-cutting on insecticide and labor.⁴ Since 1997, China increased its agricultural revenue by $990 million in 2016³⁰ The country has developed a robust regulatory and monitoring system to safeguard from GM-based risks and improve managerial practices (See table 3)^III.

Table 3.

Approved commercial/non-commercial/Trail GM crops in China

year	GM crops	Approved types	Area (million hectares)	Status
1997	GM Cotton	GK12	~3.9 million hectares	Commercially Approved
1999		GK321
1997		MON531
1998	GM Petunia Flowers	Petunia-CHS (Chalcone synthase)	Unknown	Trial
1998	GM Poplar Trees	Poplar-12 (aka Bt poplar, Populus nigra), Poplar-741 (Hybrid poplar clone)	~500 to 800 hectares	Commercially Approved
1998	GM Sweet Peppers	Sweet pepper PK-SP01	Unknown	Trial
1999	GM Tomatoes	Tomato PK-TM8805R	Unknown	Trial
2006	GM Papaya Fruit	Huanong No. 1	~8,475 ha	Commercially Approved
2009	GM Corn	BVLA430101	Unknown	Trial
2009	GM Rice	Huahui-1/TT51-1, Shanyou 63	Unknown	Trial

Source: China Biosafety Clearing House, USDA-FAS GAIN Report – China, China Ministry of Agriculture Biosafety Network

2.1.3. Philippine

Philippine is the 13^th ranked country to adopt and cultivate approved GM varieties with 0.6 million hectares of GM crops.⁴ GM crop preferred over traditional crops due to productivity and profit ratios. Recently, Department of Agriculture and Department of Environment and Natural Resources (DENR), Department of Health and (DOH) and Department of the Interior and Local Government (DILG) approved 105 events for food, feed and processing of the following crops: Alfalfa – Medicago sativa (2) events, Argentine Canola – Brassica napus (4), Cotton – Gossypium hirsutum L (12), Maize – Zea mays L (55), Potato – Solanum tuberosum L (8), Rice – Oryza sativa L. (1), Soybean – Glycine max L. (22) and Sugar Beet – Beta vulgaris (1) (see Table 4)^IV.^III

Table 4.

Approved commercial/non-commercial/Trail GM crops in the Philippine.

year	GM crops	Approved types	Area (million hectares)	Status
2014 2015 2017 2018 2019	Soybean	DAS81419-2 DP305423 x 40-3-2 DAS68416-4 DAS-44406-6 DP305423 40-3-2, MON87751 MON89788 SYHT0H2 MON89788 MON87701 FG72 x A5547-127	Unknown	Approved for imports and direct use for food, feed, and processing
2014 2015 2018 2019	Corn	MON87427 MIR162 MON88017 MON810	642,000 hectares	Commercially Approved for Cultivation
2015	Canola	RT73	Unknown	Commercially Approved for Cultivation
2015	Sugarbeet	H7-1	Unknown	Trail
2018	Oilseed rape	Ms8 Rf3	Unknown	Approved for imports and direct use for food, feed and processing
2018	Cotton	T304-40 GHB119 LL Cotton 25 GHB614 MON15985 x MON88913 Bt11 x DAS-59122-7 x MIR604 xTC1507 x GA21	Unknown	Approved for Imports and direct use for food, feed and processing

Source: Biosafety Clearing-House – Philippines, Philippines – DA-BPI Biosafety

3. Theory and Hypothesis

The term construal refers to the construction of knowledge structures that represent objects or events in an individual cognition.³¹ Every person has the unique cognition to understand, evaluate and react toward specific circumstances. Make these circumstances favorable, abstractly; psychological distance provides the different alternative to aligning the cognition of farmer with novel biotechnology according to construals. Farmer desirability of novel biotech crops involves the value of the action’s end-state (i.e. why the specific action needed), feasibility highlight the means used to reach the end state (how specific action is completed). Thus, CLT predicts that desirability has a substantial impact on feasibility as psychological distance increases. Similarly, farmer desirability has a strong impact on feasibility as psychological distance increases with construal accordingly.

Psychological distance is a central proposition of temporal construal theory suggesting high-level construal that captures the general abstract, and essential features of the objects or events, whereas low-level construal that captures the unique, concrete features of objects.³² Also, construal level is the dynamic form of temporal construal theory underlines the importance of personal cognition and environmental understanding. One of construal level theory (CLT) core concept is individual reaction to social activities dependent upon the cognitive content of activities,^33,34 although CLT³⁵ postulates the various elements of psychological distance; a few (time, space and social distance) of these have been utilized in this study considering the relevance with topic. The aspect of future temporal distance (TD) raises the queries for investing and cultivating the novel crops and food, purchasing things and saving and actions for future aims and past TD raises the question of guilt. SD highlights the social proximity with family, friends, and others. Probability raises uncertainty or doubt about novel biotechnology. Spatial distance raises the question of internet shopping or space base business. Then, at first sight, it appears that each of these psychological distance elements belong to various fields with distinct queries and solutions. Spatial distance raises the question of internet shopping or space base business. Then, at first sight, it appears that each of these psychological distance elements belong to various field with distinct queries and solutions.

CLT recommends that psychological distance is one of the most critical factors of determining the primary characteristics (desirability considerations) or secondary characteristics (feasibility considerations) on the bases of evaluation, prediction, and behavior of an individual (see Table 5). We offer a theoretical model and hypothesize a relationship between farmer intentions to adopt the approved GM crops and the psychological distance, trust behavior, as perceived by India, Philippines and The People’s Republic of China (see Figure 1).³⁵

Table 5.

Construal levels and psychological representation.

	Distant (Distal)	Near (Proximal)
Construal	High-level Construal	Low-level Construal
Description	Abstract, general	Concrete, specific
	Why	How
	Primary, central, essential	Secondary, Peripheral, Incidental
	Decontextualized	Contextual
	Schematic	Non-schematic
	Superordinate	Subordinate
	Goal related	Goal irrelevant
	Desirability	Feasibility
Psychological representations	Broader scope: The forest	Components: The trees

adopted from³⁵

Figure 1.

Theoretical Framework.

3.1. Psychological Distance: Adoption of Approved GM Crops

Psychological distance adopted in multiple areas of studies; this study focuses on the perception and emotional tendencies of farmer toward approved GM crops. Besides, the psychological distance observed a sense of uncertainty in individuals in distinct status, cultures, and values, which leads to an intimate or alienated subjective sense of connection.³⁶ In such uncertainty, CLT proposes that farmer perception might be anticipated while utilizing the psychological distance – to determine the farmer intentions to adopt the GM crops.

3.1.1. Temporal Distance (TD): Adoption of Approved GM Crops

Routine life expectations, choices, assessments and decisions frequently relate to occasions that happen near or distant future. Temporal distance affects farmer cognition and reactions to future occasions by efficiently changing the method in which they read those occasions. Temporal distances typically consider individual or group perception in term of the past and future³⁷ and dynamic environment raises the window of opportunities with time constraints: narrow window compel to the decision-makers “a need to hurry” while a full window permits leaders “to keep choices open”,³⁸ p. 141). For instance, customers had gradually good feedbacks to approved GM crops when the farmer are willing to adopt the GM crops, and temporal distance was compatible;³⁹ postulate temporal distance near future choices were more influential for proximal targets, and distant objectives were more prominent for distal future decisions. Potential farmers respond more favorably to distal future commercials containing primary attribute information (higher level construal); actual farmer reacts more positively to proximal future commercials, including secondary attribute information (low-level construal).

As recommended by,³⁵ we hypothesize TD as the perceived gap between farmer perception and adoption of GM food at present and the bridging over between farmer construal level and approved GM crops at a specific point in time in the future. Farmer (entrepreneurs) takes actions at a lower degree of abstraction considering own plausibility (e.g., financial, social and human resources) and examining probability through the market research.⁴⁰ So, based on evidence from previous literature, we suggest:

Hypothesis 1: Adoption of approved GM crops is positively related to the temporal distance, as perceived by farmers.

Hypothesis 1b: Adoption of approved GM crops is positively related to the temporal distance in the presence of trust behavior, as perceived by farmers.

3.1.2. Spatial Distance (SPD): Adoption of Approved GM Crops

The present study further conceptualize how do farmers think and make judgments to adopt the GM crops that take place in a local, regional, national, international, continent, or planet? In other words, how spatial distance from physical location affect judgments and decisions about to adopt the approved GM crops?⁴¹ Suggest that spatial distance from events increases people’s propensity to rely on construal, global, general information when forming judgments and decisions regarding those events. People use more concrete language and personal reactions to describe an event when they are spatially close to its occurrence.^38,40

Whereas customers are a more critical stakeholder for farmers associated with the cultivation of novel biotech crops as perceived to be distal from the self, a farmer is inclined to act more abstractly, consider how prospective customers can be reached and simulate strategies to attract them. On the other hand, customers are assumed to be spatially close to themselves; the farmer is likely to act less abstractly and try to engage with customers through chatting, prototype demonstrations, learning customer preferences and intent to purchase. The present research examines how farmer cognition responses to adopt the approved GM crops may rely on whether it is supposed to occur at spatially close or far. So, based on these findings, we propose:

Hypothesis 2: Adoption of approved GM crops is significantly related to the spatial distance as perceived by farmers.

Hypothesis 2c: Adoption of approved GM crops is significantly related to the spatial distance in the presence of trust behavior, as perceived by farmers.

3.1.3. Social Distance (SD): Adoption of Approved GM Crops

Psychologists such as Walter Mischel to Nira Liberman and Yaacov Trope have labeled psychological distance as a gap between yourself and other people. In the current investigation, we examine how the cognition of others actions depend upon social closeness; will help farmers to adopt the approved GM crops. Many scholars shared the concept that closeness or proximity is a social distance (e.g., see.,⁴²) For instance, in the seminal book ‘The Psychology of Interpersonal Relations,’ interpersonal similarity has been attributed as a form of social closeness; whether similarity of attitudes or personality characteristics of promoting relations between a perceiver or a target.⁴³

Social psychology recognized a number of factors, including similarities (we are closer to individuals we feel similar to ourselves), interaction frequencies (we feel closer to individuals we often see), and the reliance for outcomes (we feel closer to the individuals we rely on)^44–51,52 Moreover, social distance positively relates to the perception of farmers toward approved GM crops because of social and financial belonging.

Owing to the reason that farmers can perceive specific actions to be socially distant to the approved GM crops if few or no similar measures taken in their social networks, they can engage in extended abstract activities such as cognition (e.g. entirely reevaluating the approved GM crops). Conversely, farmers may perceive approved GM crops conduct as near to the social distance if their expanded network assists the farmers to engage in similar actions and visualize similar activities. Therefore, we suggest the following:

Hypothesis 3: Adoption of approved GM crops is significantly related to the social distance as perceived by farmers.

Hypothesis 3d: Adoption of approved GM crops is significantly related to the social distance in the presence of trust behavior, as perceived by farmers.

3.2. Moderation Effect of Passion

Identity centrality often correlates to the passion of the individual.⁵³ M. S. Living Omni media founder Martha Stewart claims, “Passion is the first and the essential ingredient for planning and launching a business.” Passion is associated with social activities that are essential for the central individual. Individual passion enhances the likelihood of psychological distance, in the context of the GM crops, to assist the farmers in cultivating the novel crops. Higher identity centrality means higher identity and activity importance to adopt GM crops.^54,55 The adoption of approved GM crops is related to higher central identities that lead to self-verification, which produces the sense of self-esteem^56,57 and results in positive affect^58,59 for the individual.

Passion is strongly inclined toward a particular activity that people firmly desire, like and consider necessary.^60,61 When farmers choose for themselves, they are more inclined to consider specific events and focus on the effectiveness in the short term. For example, in novel crops, farmer more attention is attributed to pooling funds and devising solutions for reducing the reservations of community; on other hands, who are already cultivating the approved GM crops, they are more inclined to consider abstract features, and pay more attention to long-term effect, and focus on profit and revenue. There is a similar practice for temporal distance, compared to the immediate decision, the social entrepreneurs tend to consider abstract facet for far future (a week later). Therefore we can predict:

Hypothesis 1a: Passion potentially strengthens the relationship between temporal distances and adoption of approved GM crops in the presence of trust behaviour.

Space between the participant and target customers perceived as the spatial distance.³⁵ We chose farmer as an entrepreneur and customers over other tangible and intangible venture properties because customers are the most prominent stakeholders for both small business owners⁶² and CEOs of large firms.⁶³ Customers often think about GM crops that are spatially close or far away and make decisions about them. Individual’s passion is a strong positive feeling for the entrepreneurial activities that have a meaningful and prominent effect on the entrepreneur’s (farmer) self-identity.⁶⁴ In light of these attributes, we may assume that:

Hypothesis 2b: passion potentially strengthens the relationship between spatial distances and adoption of approved GM crops in the presence of trust behaviour.

The understanding of being an entrepreneur (farmer) is the cognitive mechanism of interpretations and behavioral prescriptions of entrepreneurial identities.^65,66 Through identity theory and social psychology, all identities begin as social roles.^67,68 Social roles represent the behaviors and significance of specific social categories, such as “entrepreneur” (farmer, teacher or father). First viewing how society interprets a particular social role and provoke individuals to realize the need for GM crops. CLT proposes people perceive that activity is more concrete which is performed by themselves while the same activity is considered more abstract when performed by socially distant individuals^69,70

Similarly,⁷¹ found that customers’ choice of available products is more attractive for themselves; while they consider desirable products more attractive for others. So, we propose that:

Hypothesis 3c: passion potentially strengthens the relationship between social distances and adoption of approved GM crops in the presence of trust behaviour.

4. Methods

4.1. Sample and Data

Data for the current study collected through the convenience sampling technique from three developing countries (China, India and Philippine) through structured questionnaire and face-to-face interviews. In the case of China, 300 valid responses are used for analysis. The data collection campaign carried in December 2018 in five provinces (Anhui, Hebei, Gansu, Henan, and Shandong). For India, 350 valid responses considered from three different zones of country (North Zone, Central Zone, and South Zone). The North zone includes Punjab and Haryana, and south zone comprises Karnataka, Andhra Pradesh, and Tamil Nadu. Whereas central zone have these states Madhya Pradesh, Gujrat, and Maharashtra. In Philippines 300 valid responses collected from rural areas of Mindanao, Luzon, and Visayas, South Cotabato in Mindanao, Pampanga in Luzon and Iloilo in Visayas. We considered specific regions for each country based on the agricultural dependences of these areas where farm size varies. A small farm usually starts from 1 to 2 hectares and goes beyond 50 hectares. The data collected from three different countries with socioeconomic diversity was challenging, as the majority of farmers were illiterate. The farmers lack community platforms, and no organized database exists. To overcome these shortcomings, the questionnaires were translated into the local languages to enhance the generalizability of study.

Moreover, the study target three types of farmers: first, those who were already cultivating the approved genetically modified crops, earning profit and getting good feedback from institutions and customers. Second, those who are not growing genetically modified crops and only trust the natural crops. Third, those who want to increase crops productivity and profit. The reason behind this methodology was to access the keen perception of farmers, real responses, and to examine our model in its true spirit by CLT.

4.1.1. Dependent Variable: Adoption of Approved GM Crops

The study selected seven statements: for the adoption of genetically modified crops: two are the following (1) in your country, it is easy to cultivate genetically modified crops? (2) In your country, most farmers consider cultivating GM crops as a desirable business choice – each describing the individual cognitive passion, perception, and adoption behavioral activity captured in GEM (Global Entrepreneurship Monitor). Besides, the study also used consensus among topic experts by an amended card-sorting technique to conduct the above literature review.^72,73 It enabled us to determine the content validity and also helped us to determine what items can be included or excluded.⁷⁴

The study measures four items using a 5-point Likert scale from ‘strongly agree’ to ‘strongly disagree.’ Further to assess the reliability and validity of all items of three countries China, India and Philippine respectively by Cronbach’s alpha 0.97, 0.816, 0.884 and convergent and discriminant validity, which is in Table 7.

Table 7.

Discriminant and convergent validity.

Constructs	CR	AVE	MSV	AGMC	Passion	SD	SPD	TB	TD
China
AGMC	0.980	0.943	0.200	0.862
Passion	0.971	0.917	0.579	0.609	0.817
SD	0.941	0.841	0.293	0.513	0.466	0.844
SPD	0.989	0.969	0.415	0.652	0.612	0.641	0.872
TB	0.967	0.907	0.579	0.801	0.643	0.577	0.649	0.808
TD	0.966	0.905	0.194	0.714	0.548	0.476	0.643	0.603	0.838
India
AGMC	0.931	0.753	0.640	0.850
Passion	0.899	0.678	0.413	0.609	0.800
SD	0.899	0.748	0.428	0.543	0.493	0.865
SPD	0.901	0.744	0.428	0.652	0.600	0.654	0.801
TB	0.859	0.663	0.640	0.792	0.643	0.597	0.649	0.800
TD	0.876	0.695	0.510	0.714	0.548	0.486	0.643	0.603	0.828
Philippine
AGMC	0.910	0.733	0.510	0.842
Passion	0.901	0.753	0.413	0.620	0.867
SD	0.867	0.685	0.411	0.714	0.564	0.828
SPD	0.897	0.733	0.425	0.652	0.590	0.643	0.779
TB	0.839	0.643	0.640	0.670	0.641	0.603	0.649	0.755
TD	0.908	0.712	0.510	0.513	0.464	0.476	0.641	0.578	0.844

AGMC = approved GM crops, SD = Social Distance, SPD = Spatial Distance, TB = Trust Behavior, Temporal Distance.

Threshold values for convergent validity CR>0.7, AVE>0.5, CR>AVE, for discriminant validity MSV<AVE, ASV<AVE.

4.1.2. Independent Variables

The study utilized the items from PSED I for each of the four dimensions of psychological distance and the selection of the linguistic categorization model is to operationalize these dimensions.⁴⁰ These selections are entirely aligned with the techniques employed by numerous scholars in previous studies.^75,76 Moreover^V, for current investigation we employed five items according to our perspective to calculate the temporal distance of a respondent; three are the following: (1) How long, do you know about approved GM crops? (2) How much longer do you think it will be before these genetically modified crops are ready for market? (3) How much more time, in total would you expect to take, if other close farmers want to cultivate genetically modified crops? All the items were measured using a 5-point Likert scale, with the choices of hours, days, weeks, months and years covering 1 (most proximal) to 5 (most distant) answers. The study assessed the reliability and validity of all items of three countries China, India and Philippine respectively by Cronbach’s alpha 0.948, 0.910, 0.774 (see Table 6) and convergent and discriminant validity as given in Table 7.

Table 6.

Exploratory factor and reliability analysis.

China					India					Philippine
Items	Loadings*	CR*	α	AVE	Items	Loadings*	CR*	α	AVE	Items	Loadings*	CR*	α	AVE
Temporal Distance (TD)		0.867	0.774	0.685			0.876	0.789	0.695			0.908	0.867	0.712
TD1	0.828				TD1	0.832				TD1	0.833
TD2	0.818				TD2	0.822				TD2	0.895
TD3	0.837				TD3	0.841				TD3	0.806
TD4	0.455(Removed)				TD4	0.571 (Removed)				TD4	0.839
Spatial Distance (SPD)		0.897	0.829	0.744			0.901	0.839	0.744			0.897	0.829	0.733
SPD1	0.886				SPD1	0.891				SPD1	0.886
SPD2	0.856				SPD2	0.862				SPD2	0.856
SPD3	0.844				SPD3	0.851				SPD3	0.844
Social Distance (SD)		0.908	0.867	0.712			0.899	0.832	0.748			0.867	0.774	0.685
SD1	0.833				SD1	0.86				SD1	0.828
SD2	0.895				SD2	0.887				SD2	0.818
SD3	0.806				SD3	0.848				SD3	0.837
Passion		0.889	0.833	0.668			0.899	0.843	0.677			0.901	0.836	0.753
PA1	0.818				PA1	0.822				PA1	0.823
PA2	0.712				PA2	0.721				PA2	0.869
PA3	0.844				PA3	0.851				PA3	0.908
PA4	0.886				PA4	0.891				PA4	0.591(Removed)
Trust Behavior (TB)		0.849	0.736	0.653			0.859	0.746	0.663			0.839	0.726	0.643
TB1	0.749				TB1	0.755				TB1	0.738
TB2	0.837				TB2	0.841				TB2	0.826
TB3	0.835				TB3	0.845				TB3	0.816
Adoption of GM crops		0.92	0.884	0.743			0.931	0.894	0.753			0.910	0.874	0.733
AGMC1	0.821				AGMC1	0.831				AGMC1	0.811
AGMC2	0.906				AGMC2	0.916				AGMC2	0.884
AGMC3	0.809				AGMC3	0.819				AGMC3	0.799
AGMC4	0.909				AGMC4	0.919				AGMC4	0.887

The study relied on five items to calculate the spatial distance. The authors chose customers over other tangible and intangible venture properties because they are the prominent stakeholders for small business owners⁶² and CEOs of large firms.⁶³ The pitch that extended in this section is based on previous studies^77,78 and is as follows: ‘Within three to 4 years, what percentage of your customers do you expect to be local (located within 20 miles), regional (less than 100) and national (more than 100 miles), internationally?’. Responses are gathered using a 5-point Likert scale from 1 (most proximal) to 5 (most distant); the reliability and validity of all items of three countries China, India and Philippine are assessed through Cronbach’s alpha 0.984, 0.838, 0.829, respectively (see Table 6) and convergent and discriminant validity, which is in Table 7.

The study implied similar researcher’s items in the current investigation to measure the social distance. Four items implied in the following section: Two of them are ‘How many stakeholders have helped to cultivate GM crops as an owner or part owner?’ and ‘How many stakeholders have individually or with partners ever started to cultivate GM crops?’ The respondents have to answer according to these options 0 (none has started or helped to start a social venture) to 5 (five and above have helped to start the social venture). We transformed these options according to the 5-point Likert scale from 1 (most proximal) to 5 (most distant) by reverse coded. The reliability and validity of all the items for selected countries (China, Philippine, and India) assessed through Cronbach’s alpha (0.906, 0852, 0.867), convergent and discriminant validity as given in Table 7.

The authors selected four items from previous research work for passion (moderator) to avoid the content validity^40,53: these two are (1) Being a farmer is something I frequently think about” and “serving to the community is an integral part of who I am? (2) Being a farmer means more than just cultivating GM crops? All items measured using a 5-point Likert scale, with the choices of 1 (strongly agree) to 5 (strongly disagree). We assessed the reliability and validity of all items of three countries China, India, and Philippine via Cronbach’s alpha 0.954, 0.921, 0.833 and convergent and discriminant validity (see Table 7).

4.1.3. Mediating Variable: Trust Behavior

The authors choose four items from prior research work⁷⁹ these are (1) Generally speaking, I trust in approved GM crops (2) these approved GM crops are dependable and reliable (3) I intend to cultivate the approved genetically modified crops in the future (4) If I use approved GM crops for advancement, my productivity will increase? They were measured using a 5-point Likert scale with the choices of 1 (strongly agree) to 5 (strongly disagree). We assessed the reliability and validity of all items of three countries China, India and Philippine via Cronbach’s alpha 0.948, 0.880, 0.736, respectively, and convergent and discriminant validity (see Table 7).

4.2. Measurement

4.2.1. Factor Loadings and Convergent and Discriminant Validity

The reliability of constructs was determined through the Cronbach’s alpha to ensure the internal consistency to test the model fitness of each countries model. Cronbach’s alpha values were 0.906 to 0.948, 0.816 to 0.921, 0.736 to 0.884 for China, India and Philippine, respectively. All the observed values were higher than the recommended minimal cutoff value of 0.7⁸⁰

We followed the approach to access the convergent and discriminant validity by composite reliability (CR), average variance extracted (AVE), mean squared variance (MSV) used in^81,82 As shown in Table 6, all items loaded above 0.60 on their assigned factors and significantly associated with their specified constructs for each country. These results provided evidence of unidimensionality. Composite reliability values are greater than 0.7 in case of all three countries and the average variance extracted (AVE) for the measures ranged from 0.841 to 0.969, 0.575 to 0.914, 0.653 to 0.744 for China, India and Philippine, respectively, (see Table 7) exceeding the recommended value of 0.50 and confirming convergent validity^83,82 The maximum shared variance between any pair of constructs should be lower than the AVE for each structure to ensure discriminating validity.^84,85 The AVE value of each construct for China, India, and the Philippine was higher than the mean squared variance, which indicates that the discriminating validity is achieved. Hence, a statistically acceptable model is identified. There is no concern of convergent and discriminant validity.

4.2.2. Valuation of Model Fit

Table 8 shows the results of the goodness-of-fit measure by Standardized Root Mean Square Residual (SRMR) for PLS-SEM. The data for present study shows the satisfactory goodness of fit, China dataset shows SRMR 0.055, India dataset shows SRMR 0.069, and Philippine dataset shows SRMR 0.045, indicating that all datasets satisfy the requirements for the goodness of fit.^86,87

Table 8.

Model goodness of fit.

Saturated and Estimated Model
Data set	SRMR
China	0.055
India	0.069
Philippine	0.045

acriteria ≤0.08.

4.3. Results

It is critical to ensure that there is no concern of multicollinearity between constructs before assessing the structural model. The study depicts that multicollinearity is not a concern for all three data sets. The VIF value for China ranges from 1.387 to 2.912, India VIF ranges from 1.457 to 2.647 and Philippine VIF observed range from 1.804 to 2.496. All VIF values are less than the cutoff value of 3.0. These findings depict a higher correlation among the selected variables.⁸⁸

The structural model defines the causal relationships among the model constructs.⁸⁹ The bootstrapping method with a re-sampling of 5000 is used to estimate the significance of the path coefficient.⁸⁹ The path coefficients for China, India, and Philippine datasets have shown in Table 6.

In the Chinese and Indian perspective, hypothesis 1 indicates that farmer adoption of GM crops positively connected with the temporal distance, but for Philippine, there is no significant impact on farmer adoption of GM crops. Hypothesis 1 was accepted (β = 0.329; 0.331, p < .001, β = −0.027, rejected). Hypothesis 1a’s proposition of passion as a moderator strengthens the relationship between temporal distances and Trust behavior. Hypothesis 1a was also accepted (β = 0.121; 0.122, 0.117 p < .05) for three countries (see Table 9). The viewpoint of Chinese, Indian and Philippine, hypothesis 1b’s proposition of Trust behavior as a mediator strengthens the relationship between temporal distances and the farmer adoption of GM crops. Hypothesis 1b was also accepted (β = 0.141; 0.139, p < .001, 0.098, p < .05) (see Table 9). Hence, Hypothesis 1c’s proposition of passion strengthens farmers trust behavior for adoption of GM crops in the context of temporal distances for all three countries. Hypothesis 1c was also accepted (β = 0.067; 0.056, 0.061, p < .05) which is in Table 9.

Table 9.

Measurement of structural model path coefficients by bootstrapping.

		Chinese data		Indian data		Philippine data
	Relationship	Est.	Result	Est.	Result	Est.	Result
	Direct relationship
H1	Temporal distance →Adoption of GM crops (AGMC)	0.329aa	Accepted	0.331aa	Accepted	−0.027	Rejected
H2	Spatial distance → AGMC	0.099a	Accepted	0.087	Rejected	0.329aa	Accepted
H3	Social distance → AGMC	−0.027	Rejected	0.001	Rejected	0.099a	Accepted
	Moderation effect
H1a	Temporal distance →Passion → Trust behavior	0.121a	Accepted	0.122a	Accepted	0.117a	Accepted
H2a	Spatial distance →Passion → Trust behavior	0.114a	Accepted	0.125a	Accepted	0.104a	Accepted
H3a	Social distance →Passion → Trust behavior	−0.169a	Accepted	−0.164a	Accepted	−0.159a	Accepted
	Indirect relationship
	Mediation effect
H1b	Temporal distance →Trust behavior → AGMC	0.141 aa	Accepted	0.139aa	Accepted	0.098a	Accepted
H2b	Spatial distance →Trust behavior → AGMC	0.105a	Accepted	0.100a	Accepted	0.112aa	Accepted
H3b	Social distance →Trust behavior → AGMC	0.096a	Accepted	0.103a	Accepted	0.132aa	Accepted
	Combine effect
H1c	Temporal distance →Passion →Trust behavior → AGMC	0.067a	Accepted	0.056a	Accepted	0.061a	Accepted
H2c	Spatial distance →Passion → Trust behavior → AGMC	0.063a	Accepted	0.053a	Accepted	0.058a	Accepted
H3c	Social distance → Passion →Trust behavior→ AGMC	−0.092a	Accepted	−0.089a	Accepted	−0.079a	Accepted

aTwo-tailed significance, * = p < .05; ** = p < .001

In the Chinese and Philippine perspective, hypothesis 2 indicates that farmer’s adoption of GM crops positively connected with the spatial distance, but for Indian there is no significant impact on farmer’s adoption of GM crops. Hypothesis 2 was accepted (β = 0.099; p < .05, 0.329, p < .001, β = 0.087, rejected). Hypothesis 2a’s proposition of passion as a moderator strengthens the relationship between spatial distances and Trust behavior. Hypothesis 2a was also accepted (β = 0.114; 0.125, 0.104, p < .05) for three countries. The viewpoint of Chinese, Indian and Philippine, hypothesis 2b’s proposition of Trust behavior as a mediator strengthens the relationship between spatial distances and the farmer adoption of GM crops. Hypothesis 2b was also accepted (β = 0.105; 0.100, p < .05, 0.112, p < .001). Hence, Hypothesis 2c’s proposition of passion strengthens farmers trust behavior for adoption of GM crops in the context of spatial distances for all three countries. Hypothesis 2c was also accepted (β = 0.063; 0.053, 0.058, p < .05).

Philippine perspective hypothesis 3 indicates that farmer adoption of GM crops positively connected with the social distance, but for Chinese and Indian, there is no significant impact on farmer’s adoption of GM crops. Hypothesis 2 was accepted (β = 0.099, p < .05, β = −0.027, 0.001, rejected). Hypothesis 3a’s proposition of passion as a moderator negatively strengthens the relationship between social distances and trust behavior. Hypothesis 3a was also accepted (β = −0.169; −0.164, −0.159, p < .05) for three countries. In the case of Chinese, Indian and Philippine, hypothesis 3b’s proposition of trust behavior as a mediator strengthens the relationship between social distances and the farmer adoption of GM crops. Hypothesis 3b was also accepted (β = 0.096; 0.103, p < .05, 0.132, p < .001). Hence, Hypothesis 3c’s proposition of passion negatively strengthens farmers trust behavior for the adoption of GM crops in the context of social distances for all three countries. Hypothesis 3c was also accepted (β = −0.092; −0.089, −0.079, p < .05) which is in Table 9.

The value of R² above 0.2 regarded as comparatively high and acceptable by behavioral study norms.⁹⁰ For China, India and Philippine, the R² values for trust behavior are 0.599, 0.601, 0.545, and for farmer adoption of GM crops are 0.728, 0.718, 0.628. Further, blindfolding procedure was adapted to examine the relevance of exogenous variables and the model performance, that is just another re-use procedure.^91,92 Blindfolding is a method of combining the function fitting and cross-validation, by evaluating each construct predictive relevance by calculating changes in the criterion estimates (Q²)⁹⁰ Q² > 0 indicates the relevance of the model.⁹⁰ Our results for China, India, and Philippine of Q² indicates that farmer trust behavior toward the GM Crops (Q2 = 0.313, 0.412, 0.232) and farmer adoption of GM crops (Q2 = 0.535, 0.631, 0.405) have satisfactory predictive relevance as the values are above the cutoff level.

5. Discussion and Conclusion

This study Investigates the farmer intentions to adopt the approved GM crops from the dimensions of social, temporal and spatial distance that lead to objective rationality. It authentically and explicitly explains the psychological distance between farmer trust and intentions to adopt the novel crops. Further, the study also determines the moderating role of passion and its ability to moderate the relationship between psychological distance and trust behavior. In construal-level research, the psychological distance can be divided into space, time, and social distance, respectively.^93,94 Moreover, this research provides a comparative analysis of three data sets that shows higher consistency and contributes exclusively in enhancing the understanding of farmer’s intentions to adopt the approved GM crops that can play a vital role in the acceptance of novel food technologies.

The present study compares the three fast-developing nations datasets (China, India, and Philippine). The direct relationships between temporal distance, spatial distance, social distance, and approved GM crops depicts mix outcome. The direct relation of temporal distance and adoption of approved GM crops (TD→AGMC) accepted in Chinese and Indian dataset but rejected in Philippine dataset. Further, the relation of spatial distance and approved GM crops adoption intention (STD→AGMC) found accepted in the Philippines, and Chinese dataset and reject in Indian context. Similarly, the relation of social distance and approved GM crops adoption intention (SD→AGMC) rejected in Chinese and Indian dataset and accepted in Philippine’s dataset. These findings enhance the study consistency with the existing literature that exhibits different psychological responses based on geographical positioning.^95,96

Whereas the moderating variable passion strengthen the relationship between all psychological distance factors and approved GM crops adoption intentions across three datasets. Passion influences individual perception in the context of psychological distance to examine the farmer intentions to adopt the approved GM crops. Individual passion makes the situation more likely in the context of approved GM crops. We argued that individual cognition based on passion in near future choices was influential for proximal economic targets, and distant economic objectives were prominent for distant future decisions. We established that individual cognition based on passion has intense positive feelings to adopt the approved GM crops where spatial distance is at proximity to the self. For instance, farmers are likely to respond with low-level abstractness when customers are spatially closer to the self, such as face-to-face conversation, showing them the samples, taking feedback and providing the best services. We explored farmers feel low levels of social distance because of their engagement in concrete activities such as receiving human resources and support. Moreover, social distance negatively relates to the perception of farmers with approved GM crops owing to the sense of social belonging. Highly central identities have dominant feelings which reinforce the connection between passion, trust behavior, and farmer adoption of AGMC.

Moreover, the mediating role of trust behavior plays an incremental role in shaping farmers intentions to adopt the approved GM crops. Trust behavior mediates through all three statistical paths (TD→TB→AGMC, SPD→TB→AGMC, and SD→TB→AGMC) and plays a significant role in developing adaptive consumer intentions for novel technologies.^95–97 The finding is supported by the prior literature¹⁰⁰ and¹⁰¹ found an incremental role of trust in consolidating consumer adoptive intentions. Specifically in the GM context, the study of¹⁰² exhibits the vital mediating role of trust. Whereas current study is first to explore the trust behavior and its mediating ability between the psychological distancing characteristics and farmers intentions to adopt the approved GM crops. Further, the combined effect of psychological distance, passion, trust behavior, and AGMC were found significant. These findings further reinforce the authors claim about passion, trust and allied role in developing adoptive intentions.

The evidence also indicates the comparative nature of this research. The above evidence shows that developed countries have more resources and technological advancement in GM crops and it may spread from developed to developing and under-developing countries. The exploration and exploitation of novel biotechnology may path dependent and currently better well-known in developed countries.²⁷ While the demand for GM crops and food may be more abundant in developing and under-developing countries because of overpopulation and food shortage problems. In under develop countries farmers mostly struggle to satisfy their fundamental requirements such as living incomes, while in more advanced nations people seek opportunities to meet higher-order needs. This is well compatible with our outcomes that self-expressive results had a positive effect on of GM crops in the developing countries

Based on these relationships, we argue that farmers are passionate about economic and social activities because they associated with the verification of the high passion. These findings are novel because they directly entertain the passion of farmers who assist in converting analysis into adequate decision. This approach bolsters the path of independent research and resource allocations for farmer adoption of approved GM crops.

Theoretical Implications

The study has certain theoretical enlightenment. The statistical results of the current study extend the applicability of construal-level theory and its psychological perspectives (temporal, spatial, and social distance) ability to influence the farmers intentions to adopt approved GM crops with mediating role of trust behavior and contingent role of passion in the context of GM food and consumer behavior.

First, this study attracts our attention to the necessity of considering the moderating role of passion while investigating the farmer’s intentions to adopt approved GM crops. The PLS-SEM analysis depicts that CLT constructs, temporal, spatial, and social distance play a significant role in developing farmer’s intentions to adopt approved GM crops. Moreover, these intentions are well influenced by the moderating variable passion. Higher passion indicates higher adoption intentions.¹⁰³

Second, by integrating the CLT (temporal distance, spatial distance, and social distance), passion and trust behavior in farmer adoption intention, and this study extends the existing body of literature in marketing and GM consumption by providing a new theoretical base for investigating farmer intentions. This will open a new window for future research to examine the premarket behavioral intention in GM context.

Third, this study significantly contributes to the existing literature by theorizing the mediating role of trust behavior between CLT (temporal, spatial, and social distance) and farmer adoption intention. The findings of this study confirm our argument that the farmer intentions to adopt GM-approved crops are mediated by trust behavior.

Finally, this study highlights the importance of psychological distance through construal-level theory and suggests that adoptive farmer intentions are influence by CLT constructs. These findings offer different strategic opportunities to the businesses to modify their GM business plans to meet the current premarket intentions of farmers.

Practical Implications

This study has certain critical practical implications based on the above statistical and discussion-based conclusions. First, new GM cultivating farmers differently perceive psychological distance with construals and to improve psychological distances adequate action could be taken. The study suggests the policymakers to encourage the farmers through active information exchange and collaborate to cultivate the approved GM crops. This will align the cognitive process with alternative space, different time contrast and socially. Conversely, study discourages the deviation in farmer cognition that arises from the social media, print media and peer reviews.

Second, agri education and awareness campaigns to spread the necessary information to ordinary farmers are of prime importance. This study suggests that awareness about GM crops plays an incremental role in reducing psychological distances such as farmer GM fear and misconceptions, instead highlights GM crops profitability and ability to reduce the food shortage.

Third, the agri-business managers can encourage the farmers through scientific and economic evidence to overcome the psychological fears. These real-time social interactions between the managers and farmers can provide opportunity to businesses and individual farmers to establish trust in GM context.

Last, we may highlight the expected farmer’s adoption of approved GM crops. Thus, we suggest that farmer readiness to adopt GM crops will shape agricultural economic development with different construal accordingly. For instance, incubators, who are cultivating the approved GM crops, will decrease the imaginary cognition of conventional farmers by producing the handsome quantity of the crops as well as profit.

Limitations and Future Scope

Initially, we focused on three psychological distance dimensions, passion, trust behavior and approved GM crops at the individual level. Distributed cognition may have weakened or strengthened the connections found¹⁰⁴ at the collective and organizational levels. Future research may consider collective or group, cultural and ethnic elements affecting individual cognition. Third, further studies may test the personality oriented factors to test the moderating and mediating effect related to GM crops. Moreover, future studies may use other data analysis techniques like fsQCA which can offer new insights.

Acknowledgments

We acknowledge Dr Krishna Harshavardhan Gullapalli, Dr Wen Bo and lecturer Zhang Wen Juan for helping to collect the questionnaire from India, China and Philippine respectively. Authors are grateful to all members who helped to collect the data for this research paper.