Building Trustworthy Relationships with Smallholder(Small-scale) Agro-commodity Suppliers: Insights from the Ghana Cocoa Industry

Abstract

The purpose of the study is to investigate which factors lead firms should consider in their quest to build trustworthy supply relationships with agro-commodity suppliers. We developed a model of opportunism-trust relationships, which we analyzed in the context of a smallholder agro-commodity supply market (SHACSM). The data source is a survey of 444 buyer-supplier relationships from the cocoa industry of Ghana. The analysis shows that relational satisfaction, cooperation and information exchange reduce perceptions of opportunism consistent with the literature. However, multigroup analysis suggests differences in perception between men and women farm owners/managers. While men perceived the important role of information exchange in reducing perceptions of opportunism, women farm owners/managers were more concerned about the negative consequence of opportunism on trust. We discuss implications for theory, public policy, and macromarketing practice, and suggest options for future research.

Keywords

supplier relationships agricultural marketing commodity supply/value chain governance opportunism small suppliers macromarketing gender

Introduction

The global value chain (GVC) is a useful concept for describing and analysing the international and geographical fragmentation of contemporary supply chains (Gereffi and Lee 2012; Gibbon, Bair, and Ponte 2008). The cocoa value chain is a typical example of a global commodity value chain, characterised by a network of labour and production processes. A commodity chain is a set of inter-organisational networks clustered around one commodity or product; it could be producer-driven or buyer-driven (Gereffi, Humphrey, and Sturgeon 2005). The GVC concept originated in a framework called the global commodity chain, linking the concept of value-added chain to the global organisation of industries with a focus on value creation across all the activities in the chain (Gereffi and Lee 2012).

In agro-commodity value chains, critical links occur between farm businesses as suppliers and buyers. Suppliers of agro-commodities, such as cocoa, are usually smallholder farmers geographically spread across tropical countries, forming part of an increasingly complex chains of supply and demand (Glavee-Geo 2019). The term smallholder farms refer to small farm enterprises averaging five hectares, typical of most cocoa farms in West Africa. State exporting marketing monopolies usually held the major roles in these chains, exercising control through setting prices and price stabilisation. These chains, characterised by national regulation and institutions, such as international commodity exchanges and futures markets (Varangis and Schreiber 2001), have seen changes in the country of origin. These changes reflect the types of relationships that suppliers have with commodity buyers in different markets, ranging from fully liberalised to less liberalised markets.

Government organizations such as agri-food marketing boards set prices and allocate supplies to markets, among other functions. This has an impact at the societal level and falls under the domain of macromarketing (Nason 1988; Peterson and Zehra 2018; Shapiro 2006). Recent studies (e.g. Vargo et al. 2017) recommend system thinking in terms of wholes, relationships, processes, and patterns regarding markets. Analysis at the aggregate level in the study of agricultural marketing systems (especially smallholder agro-commodity supply market –SHACSM) in developing countries, presents us with an increased understanding of macromarketing issues.

The average per capita income of cocoa growers is below $2 per day (Oomes et al. 2016). Often, the phrase “bottom of the pyramid” (BOP) is used to describe the 4 billion people globally who are living on $5 or less per day (Fawcett and Waller 2015, p. 233). Seventy percent of the most deprived live in rural areas and survive on less than $1.25 a day. The most impoverished members of agrarian societies in developing countries are often subsistence farmers who rely on survivalist activities to generate income (Littlewood and Holt 2014, p. 106). These communities are at the BOP (e.g., Karnani 2007), characterised by extreme poverty with limited access to goods and services (Peterson and Zehra 2018).

However, the cultivation of cash crops (e.g., cocoa, coffee, and cotton) has provided opportunities to earn a sustainable livelihood. Sustainability is essential if poverty reduction is to be long-lasting (Peterson 2013; Peterson and Zehra 2018). Various factors inhibit the efficient and successful establishment of sustainable and inclusive value chains involving smallholders. Moreover, current evidence regarding factors that influence trust-building between businesses or their agents and smallholder agro-commodity suppliers (SHACS) is scarce. While we know that satisfactory and trustworthy relationships are important prerequisites for any successful business relationship the literature is silent on the role of gender and whether men and women small-scale farm owners/managers may have different perceptions of factors that influence perceived opportunism and its consequential outcome regarding trust.

The purpose of this paper is to highlight the factors lead firms should consider in their quest to build trustworthy supply relationships with agro-commodity suppliers. Trust is important to sellers in emerging markets because suppliers are in a vulnerable relationship as compared to buyers due to the fragmented nature of the smallholder agro-commodity supply market (Dadzie, Dadzie, and Williams 2018). Challenges confronting agro-commodity value chains include market imperfections, scarce resources, lack of transparency, and ethical dilemmas (Goyal, Sergi, and Jaiswal 2015). These markets also tend to have “informal” exploitative intermediaries, which further raises costs (Tarafdar, Anekal, and Singh 2012). This article seeks answers to the following research questions:

RQ1: Which factors influence trust-building in supply markets with numerous smallholder suppliers in a developing economy?

RQ2: Do women and men small-scale farm owners/managers perceive the antecedents and outcome of opportunism differently?

RQ3: What are the implications for public policy and macromarketing practice?

This study offers important theoretical contributions and practical implications concerning value chain governance. Our results provide useful insights to top management, supply chain managers, commodity-sourcing managers, and policymakers in government, non-governmental and international institutions. The paper aims to add to a comprehensive theory regarding the role of marketing in society anchored on the premise of inclusive growth and sustainability (Sheth 2011). It highlights how best to deal with intermediaries and agro-commodity suppliers and how to confront challenges that limit the full potential of smallholder farmers’ inclusiveness and value-adding initiatives. The paper is organised as follows: theory review and hypotheses development followed by method, data analysis, and results. The article ends with a discussion, implications, and conclusion.

Theory Review and Hypotheses Development

Theories of Economic and Social Behaviour in Explaining Exchange Relationships

Transaction cost economics (TCE; e.g. Williamson 1985) and relational contracting (e.g., Macaulay 1963; Macneil 1980) are two important theoretical foundations for understanding exchange transactions and business relationships. TCE focuses on efficiency, with the main objective of minimising total cost, while relational contract theory extols the role of relational norms as a key governance mechanism by relying on behavioural features such as trust, commitments, reputation, and social norms (Heide 1994; Macneil 1980; Morgan and Hunt 1994). Social exchange theory posits that parties enter and maintain relationships with the expectation that this will be rewarding for each party (Blau 1968; Homans 1958), positive outcomes over time increasing trust and commitment (Lambe, Wittmann, and Spekman 2001; Morgan and Hunt 1994). “Positive outcomes over time produce relational exchange norms” (Lambe, Wittmann, and Spekman 2001, p. 11). Norms are explicit or tacit, mutually agreed-upon rules of behaviour that govern exchange relationships. “Trust exists when one party to the relation believes the other party has an incentive to act in his or her interest or to take his or her interests to heart” (Cook, Hardin, and Levi 2005, p. 2).

Trust is the willingness to be vulnerable to the actions of another party. Trust is based on the expectation that the other party will perform an action important to you, irrespective of your ability to monitor or control the other party (Xu, Cenfetelli, and Aquino 2016). Trust matters the most when the uncertainty (e.g., complexity and ambiguity) of unmet expectations is high or when the vulnerability of control (e.g., failure of formal contract) is high. It also matters when long-term interdependence (e.g., reciprocal relationship) and the stakes (e.g., financial loss) of unmet expectations or control failure are high (Ping Li 2012). An agency relationship exists whenever one partner (i.e., the principal) depends on another (i.e., the agent) to undertake some action on the principal’s behalf (Bergen, Dutta, and Walker Jr. 1992; Eisenhardt 1989). In this study, the perceptions of opportunism mainly concern the purchasing agents who represent the buying firms and are intermediaries between cocoa growers and licensed buying companies (LBCs). The LBCs are the principals, while the purchasing officers are the agents. The research context includes cases of unethical behaviour by some purchasing officers who under-estimate/value sales from cocoa growers. Trust is a crucial element of the exchange process when the likelihood of opportunism is high. The perceived trustworthiness of the agents of firms in various types of economic exchanges arguably have positive effects, creating greater flexibility, more sharing of information, and under some circumstances, reduced transaction costs (Cook, Hardin, and Levi 2005).

Trust works primarily at the interpersonal level to produce micro-level social order and lower the costs of monitoring and sanctioning that might be required were individuals untrustworthy. Trust plays an important role in informal social exchange. It decreases the need for regulation by state and other institutions – in terms of monitoring – and reduces transaction costs (Cook, Hardin, and Levi 2005). Mutual reciprocation of beneficial action over time through multiple interactions creates trust. The belief that the other party will not take unfair advantage or exploit the relationship is the essence of a trustworthy relationship (Blau 1968; Homans 1958; Lambe, Wittmann, and Spekman 2001).

Research Model and Hypotheses

We chose the relationship variables modeled in this study after preliminary qualitative inquiry. The problem of perceived opportunistic behaviour by purchasing agents and the impact such deteriorating relationships have on the local business community became obvious. We developed a theoretical model for testing within the empirical setting. The research model is shown in Figure 1. It relates buyer-supplier cooperation positively with relational trust and buyer-supplier relational satisfaction but negatively with buyer opportunism. Relational satisfaction is expected to inhibit perceived buyer opportunism and enhance relational trust. However, perceptions of opportunism impede trust. Information exchange is expected to diminish perceptions of opportunism while stimulating trust building. The research model also shows that power asymmetry and relationship duration could influence buyer opportunism and buyer-supplier relational trust. Power is important for effective coordination, where weaker chain members may be willing to tolerate imbalanced relationships if there are sufficient gains (Hingley 2005; Maglaras, Bourlakis, and Fotopoulos 2015). We controlled for sales volume, gender, membership of cooperative and size of farm since these variables could provide some alternative explanation of relational trust. The following subsections give the rationale for the hypotheses based on theory and previous empirical research.

Figure 1.

Conceptual model.

The impact of buyer-supplier cooperation

Cooperation occurs when parties work together to achieve mutual goals (Barnes, Yen, and Zhou 2011; Morgan and Hunt 1994). Distrust can create barriers to cooperation (Cook, Hardin, and Levi 2005). The relationship between cooperation and trust is positive (Anderson and Narus 1990; Morgan and Hunt 1994). Therefore, effective collaboration and cooperation are important for enhancing trust in business relationships (Zineldin and Jonsson 2000). Based on the perspectives of suppliers and buyers in the context of the Korean telecommunication industry, Kim et al. (2010) suggest that while inter-organisational trust is a significant determinant of cooperation for buyers, this was not so for suppliers. Parkhe’s (1993) study of the structuring of strategic alliances found support for cooperation as an antecedent to opportunism.

Cooperation reflects harmony and conflict resolution; by seeking cooperative solutions, the parties involved feel satisfied that they can maintain harmony (Barnes, Yen, and Zhou 2011). Channel members need to understand how cooperation is developed and maintained to experience satisfying, long term relationships (Skinner, Gassenheimer, and Kelly 1992). The benefits of cooperation not only include social harmony, but also improvements in performance and economic outcomes. Suppliers that perceive better cooperation are more likely to be pleased with the relationship (Anderson and Narus, 1990; Jonsson and Zineldin, 2003). An underlying assumption behind partnerships is that cooperation improves performance satisfaction – a direct and positive association demonstrated in several studies (Graca, Barry, and Doney 2015; Park, Vertinsky, and Lee 2012). We expect similar results in the context of buyer-SHACS exchanges. Hence, we proposed that:

H₁: Buyer-supplier cooperation has a positive effect on relational trust (H_1a ), buyer-supplier relational satisfaction (H_1b ), and a negative impact on buyer opportunism (H_1c ).

The impact of buyer-supplier relational satisfaction

Buyer-supplier relational satisfaction is defined as “a positive affective state resulting from the appraisal of all aspects of a firm’s working relationship with another firm” (Anderson and Narus 1990, p. 45). It reflects “a party’s cognitive state of feeling adequate or inadequately rewarded for the sacrifice undergone in facilitating that relationship” (Frazier 1983, p. 74). Gassenheimer, Baucus, and Baucus (1996) confirm that opportunistic behaviour reduces franchisee satisfaction in the fast-food industry. When an exchange partner acts opportunistically, the social (and perhaps economic) rewards are reduced over a period. Social exchange theory explains why parties to such an exchange may choose to terminate the relationship, even if the economic rewards or benefits of a new, more socially acceptable relationship are diminished (Hawkins, Wittmann, and Beyerlein 2008, p. 897). A meta-analysis conducted by Crosno and Dahlstrom (2010) finds support for the negative association between satisfaction and opportunism.

Social relations generate trust in exchange relationships as individuals with whom one has a continuing relationship have the economic motivation to be trustworthy (Buvik and Reve 2002; Granovetter 1985). Trust is posited as an antecedent of satisfaction by some researchers (e.g., Rodriguez, Agudo, and Gutierrez 2006), while others posit satisfaction as an antecedent of trust (e.g., Geyskens, Steenkamp, and Kumar 1999; Selnes 1998). In a study of 174 Spanish industrial firms, Sanzo et al. (2003) find support for the positive association between trust and the buyer firm’s satisfaction with the supplier. Based on the above discussion, we propose that in the context of a smallholder agro-commodity supply markets:

H₂: Buyer-supplier relational satisfaction has a positive effect on relational trust (H_2a ) and a negative effect on buyer opportunism (H_2b ).

The impact of buyer opportunism

Opportunism refers to self-interested behaviour with guile (Williamson 1985). According to Williamson (1985, p. 47), opportunism comprises of “calculated efforts to mislead, distort, disguise, obfuscate or otherwise confuse”. An opportunistic partner may use deceit to take advantage of a transaction. Opportunism affects the trustworthiness of one partner and decreases the other’s trust (Saleh, Yunus, and Andaleeb 2014). A meta-analysis conducted by Crosno and Dahlstrom (2010) found support for the negative association between satisfaction and opportunism. Ashnai, Henneberg, and Naudé (2016), using a fuzzy set qualitative comparative analysis (fsQCA) reported that in cases where relationship-specific investments drive inter-organisational trust, this must be complemented by the absence of opportunism or by interpersonal trust. Hence, in the context of a smallholder agro-commodity supply markets:

H₃: Buyer opportunism has a negative effect on buyer-supplier relational trust.

The impact of information exchange

Information exchange that enhances inter-organisational processes is a key predictor of overall performance (Gligor and Autry 2012). Information exchange is the “formal as well as informal sharing of meaningful and timely information between firms” (Anderson and Narus 1990, p. 44). Rapid exchange of information stimulates a trustworthy working relationship by helping in problem resolution and in aligning perceptions and expectations (Moorman, Deshpande, and Zaltman 1993). Yen, Wang, and Horng’s (2011) study of the electronics industry in Taiwan, found support for the significant effect communication has on trust. Information exchange (i.e., being frequent, timely, relevant, and reliable) enhances trustworthiness (Anderson and Weitz 1989; Morgan and Hunt 1994). However, the literature argues that if exchange partners are unaware of the antecedents of trust, communication being one, this may create a sense of mistrust and hinder the development of the relationship due to asymmetry in power relations (Viitaharju and Lähdesmäki 2012). Information exchange is an important antecedent of opportunism. Deeds and Hill (1999) show perceived information sharing at the executive level had a negative impact on perceived performance of research alliances in the biotechnological industry and the other partner’s perceived opportunism. Therefore, we propose that:

H₄: Information exchange has a negative effect on buyer opportunism (H_4a ) and a positive impact on buyer-supplier relational trust (H_4b ).

We further argue that the effect of information exchange on trust could be mediated by opportunism. Information exchange precedes trust formation. When buying agents fail to share timely and meaningful information with their partners (herein the cocoa suppliers), this is likely to enhance perceptions of opportunism and consequently lead to mistrust. Hence, we propose that:

H₅: The effect of information exchange on relational trust is mediated by buyer opportunism.

Gender’s role in shaping perceptions of opportunism

Moore and Buttner (1997) and Ratten (2017) found that most studies, assuming entrepreneurs to be male, focus on this gender. Accordingly, women in business are mostly associated with weaker characteristics (Ratten 2016). For example, “The more subtle female characteristics, such as softness and empathy, have been considered less suitable for business” (Ratten 2017, p.3). Businesses run by females usually have unique features that differentiate them from male-run businesses. This is due to females valuing a more conducive environment based on trust and interaction (Bruni, Gherardi, and Poggio 2004; Ratten 2017). Gender has a direct and indirect effect on entrepreneurial intentions and hence, on business performance (Noguera, Alvarez, and Urbano 2013; Ratten 2017). Communication is useful for coordinating economic exchanges and is a critical determinant of relational governance (Sheng et al. 2006). According to Sanchez-Franco, Ramos, and Martin Velicia (2009), mens’ perceptions of value in an information process is based mainly on its effects on their performance; men display a higher degree of extrinsic orientation in their motivation than women. Subsequently, we argue that the role of information exchange in dissipating perceptions of opportunism is stronger for men than for women. We hypothesise that:

H₆: The negative effect of information exchange on perceptions of opportunism differs by gender such that for men farm owners/managers, the effect is stronger.

Small-scale farmers can cooperate to mitigate the power or opportunism of the MNEs and their agents. Meier zu Selhausen (2016) found that women’s active participation in agricultural-marketing cooperatives and collective action enabled them to mitigate socio-economic constraints. Pavlou, Liang, and Xue’s (2007) study on buyer-seller relationships in business-to-customer (B2C) e-commerce illustrates that information asymmetry between buyers and sellers is negatively related to the buyer’s trust in the seller and positively associated with fear of an opportunistic seller. In smallholdings, women farm owners or managers are marginalized by various socio-economic constraints (Meier zu Selhausen 2016), and they are more likely to experience the negative impact of opportunistic buying agents than men. Such experiences may lead to women having less trust in buyer-seller relationships and exchanges. Given the above and earlier deliberations, we hypothesize that:

H₇: The negative effect of perceptions of opportunism on trust differs by gender, such that for women farm owners/managers, the effect is stronger.

Method

Empirical Setting

The research setting is the Ghanaian cocoa supply market, a typical developing and emerging market context. We selected this for several reasons. First, in the supply market, the issue of trust between smallholder agro-commodity suppliers and buying firms is critical in understanding local business relationships in less developed market economies. For example, the financial loss of inaccurate weighing of produce can be a source of cognitive distrust (Dadzie, Dadzie, and Williams 2018). This has implications for management and issues of public policy in the domain of macromarketing (Dadzie and Sheth 2018; Nason 1988).

Second, the global cocoa market is valued at $2.1 billion, and the worth of the chocolate market is projected to be around $131 billion by 2019. Ghanaian cocoa farmers are among the world’s top ten producers, making Ghana among the world’s top ten cocoa-producing countries (Oomes et al. 2016). As the second leading exporter of cocoa to world markets in the USA, Europe and Asia, Ghana’s cocoa industry offers a good empirical setting to understand how trust can be leveraged to enhance relationships with suppliers/customers (Dadzie, Dadzie, and Williams 2018). This context gives validity to our research and strengthens the generalisability of our results (see sample characteristics in Table 1). Third, the Ghanaian cocoa industry is dominated by local buying firms (known as licensed buying companies – LBCs). Produce Buying Company, formerly state-owned, has the largest share of the market (31%); the rest of the market is evenly divided between a large number of local buying companies and a few international cocoa buyers. Our empirical data help in providing an understanding of how cocoa suppliers in the local market are related to buyers in a national supply market that is integrated eventually into an international setting.

Table 1.

Sample Characteristics (n = 444).

Demographic characteristics	Category	Frequency	Percent
Gender	Female	163	36.7
Gender	Male	281	63.3
Age	Below 30	22	5.0
	31-40	56	12.6
	41-50	115	25.9
	Above 50	251	56.5
Size of farm enterprise (Hectares)	1-5	286	64.41
	6-10	110	24.77
	11-15	25	5.63
	16-20	14	3.15
	21-25	7	1.57
	26-30	2	0.45
Relationship duration (years)	1-5	251	56.53
	6-10	128	28.82
	11-15	42	9.46
	16-20	15	3.38
	21-25	5	1.13
	26-31	3	0.67
Annual sales volume (number of bags per 62.5kg)	Less than 5	229	51.57
	6-10	128	28.83
	11-15	34	7.66
	16-20	28	6.31
	21-25	6	1.35
	26-30	9	2.03
	Above 31	10	2.25
Membership of cooperative	Yes	143	32.2
Membership of cooperative	No	301	67.8

All the LBCs follow a sourcing business model where they earn revenue based on how much they can source from the farms (Cocobod 2019; Glavee-Geo 2019). All the local LBCs have direct contact with cocoa farmers via their purchasing officers or agents. This direct link validates the responses provided by the participating farmers. The unit of analysis is the relationship between the cocoa farmer and its most important buying firm.

Data Collection

Before designing the structured questionnaire, we conducted interviews with local cocoa farmers to become familiar with their perspective. Data collection through mail or e-mail, results in low participating percentage in developing economies. There are over 800,000 cocoa farms in Ghana (Cocobod 2019), mostly family-owned small-to-micro businesses (Glavee-Geo 2019). The cocoa farmers we selected have sold their annual cocoa crop production to one specific LBC for many years (> 1 year). We applied the key informant approach (John and Reve 1982) to collect primary data (via the questionnaire) from these cocoa farmers who were well conversant with the research problem. In this study, the key informants were the owners of the farm businesses, or farm managers who were knowledgeable about the operations of the farm. The sampling was based on farms located in the southern part of Ghana according to knowledge of the industry from the industry regulator. Consent was sought from each respondent before each interview. Subsequently, primary data were collected through face-to-face interviews over three weeks. The interviews were conducted in the cocoa-growing regions of Central, Eastern, and Ashanti regions. The key informants were mostly farm owners who were interviewed at their households (sometimes with a farm manager providing corroborative information). The sample size was 555, with an overall response rate of 87.7% (487 completed surveys) and effective response rate of 80% (444 accurately completed surveys).

Measurement

The research model consists of eleven latent variables, six of which were measured by multiple items. Items were adapted from literature to preserve content validity; however, the wording of each was modified to suit this study. Buyer-supplier cooperation consists of three items adapted from Anderson and Narus (1990). The three questions for information exchange were adapted from Heide and Miner (1992). However, buyer opportunism – adapted from Skarmeas, Katsikeas, and Schlegelmilch (2002) and John (1984) – has seven items. The power asymmetry construct has three questions from Joshi and Stump (1999) and Anderson and Weitz (1989). The five items of buyer-supplier relational satisfaction were adapted from Benton and Maloni (2005), while the seven buyer-supplier relational trust items are from Morgan and Hunt (1994) and Moorman, Deshpande, and Zaltman (1993). The items, their sources, mean, standard deviation, and loadings are listed in Table 2. Also, five single variables – relationship duration, sales volume, the informant’s gender, membership of cooperative and size of farm – are used as controls (see also Figure 1 and Table 1).

Common Method Variance

First, we assessed common method variance (CMV) (Podsakoff et al. 2003) by using Harman’s (1976) single-factor method, followed by the marker variable procedure (e.g., Lindell and Whitney 2001; Malhotra, Kim, and Patil 2006). The single factor that emerged from the unrotated factor solution accounted for 27.32% (< 50%). As a rule, if a single factor accounts for more than 50% of the variance, there is a higher probability that CMV exists (Podsakoff and Organ 1986). In addition, the marker variable technique was used. A marker variable is a variable that is theoretically distinct and unrelated to at least one other variable in the study. Several marker variables were used (e.g., age of the key informant) to estimate the loadings on every item in the partial least squares (PLS) path model, and each item’s loadings on its theoretical construct were observed. The estimated path model relationships were compared with and without the marker. All theorized paths maintained their level of statistical significance, showing that CMV bias is unlikely to influence the findings of the study.

Data Analysis

The analytic technique of choice is variance-based structural equation modeling, using SmartPLS 3.0 (Ringle, Wende, and Becker 2015). First, the psychometric properties of the measures were evaluated by conducting an exploratory factor analysis. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was .88, and Bartlett’s test of sphericity was significant (approximate chi-square = 11095.46, df = 1540, p = .001), indicating that the dataset was appropriate for factor analysis. Table 2 shows the factor loadings (> .70) of the PLS analysis of the measurement model. Convergent and discriminant validity were assessed based on Fornell and Larcker (1981). The composite reliability and Cronbach’s alpha values for all constructs exceeded the acceptable value of .70 (Hair et al. 2017). Average variance extracted (AVE) value of .50 indicates an acceptable level (Fornell and Larcker 1981) for convergent validity. The AVE ranged from .69 to .82 (see Table 3).

Table 2.

Construct, Indicators, Descriptive Statistics and Loadings (n = 444).

Construct	Question	Indicator	M	SD	Loadings#
Buyer-supplier cooperation Anderson and Narus (1990).	The buying company cooperates closely with our farm to make this/our relationship work.	CN1	5.02	1.66	0.875***
	The buying company cooperates closely with our farm to fulfil our genuine business requests.	CN2	5.22	1.28	0.864***
	The buying company cooperates closely with our farm to complete joint business activities.	CN3	5.28	1.25	0.747***
Information exchange Heide and Miner (1992).	The buying company frequently share information about cash bonuses with our firm.	IN1	5.26	1.32	0.835***
	The buying company frequently provide information that helps our firm business interests.	IN2	5.23	1.32	0.863***
	The buying company frequently share information that affects our relationship.	IN3	5.32	1.29	0.848***
Buyer opportunism ## Skarmeas et al. (2002), John (1984).	The buying company often pays less cash for the supplied cocoa beans.	OP1	4.38	1.92	0.869***
	The buying company often pays less cash bonus than I deserve.	OP2	4.62	1.89	0.917***
	The buying company often undervalues my cocoa beans.	OP3	4.68	1.94	0.910***
	The buying company often underrates the quality of my cocoa beans.	OP4	4.31	1.93	0.906***
	The buying company often overlooks to correct sales’ errors in my transactions.	OP5	4.41	1.86	0.916***
	The buying company often weighs less than the actual weight of my cocoa beans.	OP6	4.58	1.86	0.889***
	The buying company often pays less cash bonus than I deserve.	OP7	5.60	1.92	0.910***
Power asymmetry Joshi and Stump (1999) Anderson and Weitz (1989).	The buying company enjoys more power in our relationship (owing to my small sales volume).	PA1	5.38	1.43	0.855***
	The buying company enjoys more power in our relationship because the volume % supplied is small.	PA2	5.50	1.36	0.921***
	The buying company enjoys more power in our relationship because my cash bonus % is small.	PA3	5.47	1.45	0.798***
Buyer-supplier relational satisfaction Benton and Maloni (2005).	I have a satisfying relationship with this buying company.	RS1	4.76	1.49	0.854***
	I have satisfactory dealing with this buying company.	RS2	4.75	1.58	0.906***
	I continue to sell to this buying company because of the high satisfaction level.	RS3	4.67	1.62	0.926***
	I am satisfied with the ways this buying company relates to me.	RS4	4.66	1.61	0.917***
	I am satisfied with the business dealings of this buying company.	RS5	4.71	1.65	0.905***
Buyer-supplier relational trust Morgan and Hunt (1994), Moorman et al. (1993).	I trust this buying company weighs my cocoa sales correctly.	TT1	4.55	1.72	0.879***
	I trust this buying company enters my cocoa sales correctly.	TT2	4.51	1.81	0.921***
	I trust this buying company documents my sales transactions correctly.	TT3	4.46	1.93	0.915***
	This buying company enjoys high business integrity.	TT4	4.57	1.92	0.904***
	This buying company actions are trustworthy.	TT5	4.41	1.83	0.931***
	I trust the sincerity of this buying company.	TT6	4.29	1.81	0.899***
	I trust this buying company keeps an accurate record of my sales transactions.	TT7	4.33	1.70	0.865***

Note: # Based on 10000 bootstrapping samples *** p < 0.001 (two-tailed), ## Opportunism questions are negatively worded and reversed.

Table 3.

Reliability, Average Variance Extracted (AVEs) and Discriminant Coefficients (n = 444).

Construct	Composite reliability	Cronbach’s Alpha	AVE	1	2	3	4	5	6
Buyer-supplier cooperation (1)	0.87	0.78	0.69	0.83
Information exchange (2)	0.89	0.81	0.72	0.39	0.85
Buyer/agent opportunism (3)	0.97	0.96	0.82	-0.26	-0.24	0.90
Power asymmetry (4)	0.89	0.82	0.74	0.06	-0.05	0.19	0.86
Buyer-supplier relational satisfaction (5)	0.95	0.94	0.81	0.41	0.28	-0.30	0.10	0.90
Buyer-supplier relational trust (6)	0.97	0.96	0.81	0.45	0.29	0.57	-0.06	0.45	0.90

Note: Bold numbers on the diagonal shows the square root of the AVEs; Numbers below the diagonal represent construct correlations.

Discriminant validity was assessed using Fornell and Larcker’s (1981) approach. Discriminant validity indicates the extent to which a given construct is different from other latent constructs. A comparison of the square root of the AVE (diagonal values) and the correlations among the constructs presented in Table 3 meets Fornell and Larcker’s (1981) criterion in support of discriminant validity. Further examination of indicator cross-loadings (see Table 4) provides further demonstration of convergent and discriminant validity, in which all constructs were more strongly correlated with their own measures than with any other constructs. In addition, we used the multitrait–multimethod matrix to assess discriminant validity: the heterotrait-monotrait ratio of correlations (HTMT) (Henseler, Ringle, and Sarstedt 2015). The HTMT values were below .85, demonstrating that discriminant validity is established between any two of the constructs (Hair et al. 2017; Hair et al. 2018; Henseler, Ringle, and Sarstedt 2015). Based on the above evaluations, we concluded that all the constructs show evidence of acceptable validity.

Table 4.

Demonstrating Discriminant Validity using Cross-loadings.

	Buyer-supplier cooperation	Informationexchange	Buyer/agent opportunism	Powerasymmetry	Buyer-supplier relationalsatisfaction	Buyer-supplier relationaltrust
CN1	0.875	0.331	-0.252	0.084	0.387	0.483
CN2	0.864	0.335	-0.215	0.004	0.332	0.331
CN3	0.747	0.301	-0.152	0.071	0.278	0.258
IN2	0.330	0.835	-0.172	-0.047	0.261	0.232
IN3	0.310	0.863	-0.219	-0.040	0.227	0.212
IN4	0.343	0.848	-0.218	-0.043	0.225	0.281
OP1	-0.167	-0.197	0.869	0.184	-0.222	-0.496
OP2	-0.234	-0.250	0.917	0.212	-0.273	-0.524
OP3	-0.258	-0.214	0.910	0.128	-0.264	-0.533
OP4	-0.250	-0.225	0.906	0.158	-0.274	-0.503
OP5	-0.251	-0.239	0.916	0.167	-0.300	-0.537
OP6	-0.226	-0.202	0.889	0.150	-0.301	-0.519
OP7	-0.222	-0.190	0.910	0.177	-0.247	-0.506
PA1	0.070	-0.006	0.162	0.855	0.133	-0.060
PA2	0.025	-0.078	0.182	0.921	0.036	-0.057
PA3	0.085	-0.044	0.130	0.798	0.107	-0.019
RS1	0.386	0.235	-0.255	0.071	0.854	0.379
RS2	0.401	0.287	-0.252	0.098	0.906	0.377
RS3	0.397	0.278	-0.304	0.124	0.926	0.456
RS4	0.319	0.219	-0.244	0.093	0.917	0.384
RS5	0.324	0.232	-0.284	0.072	0.905	0.417
TT1	0.385	0.311	-0.523	-0.072	0.363	0.879
TT2	0.388	0.268	-0.525	-0.053	0.428	0.921
TT3	0.438	0.239	-0.518	-0.052	0.442	0.915
TT4	0.379	0.214	-0.537	-0.074	0.366	0.904
TT5	0.388	0.278	-0.526	-0.051	0.408	0.931
TT6	0.414	0.252	-0.464	-0.021	0.436	0.899
TT7	0.439	0.255	-0.523	-0.026	0.386	0.865

Note: Bold values significant at p < 0.001.

Results

H_1a stated a positive association between buyer-supplier cooperation (BSC) and buyer-supplier relational trust (BSRT). The results indicate support for the positive effect of BSC on BSRT (β = .24, p < .001, t = 5.60). Additionally, the positive association (see H_1b) between BSC and buyer-supplier relational satisfaction (BSRS) is also strongly supported (β = .41, p < .001, t = 9.55), while H_1c, which states a negative association between BSC and buyer opportunism (BUO), is also supported (β = –.13, p < .05, t = 2.56). H_2b proposed a negative association between BSRS and BUO, which is supported (β = -.23, p < .001, t = 4.71). We hypothesised (see H_2a) that BSRS has a positive effect on BSRT, and this was found to be strongly supported (β = .23, p < .001, t = 5.13). H₃, stated that buyer opportunism (BUO) is negatively related to buyer-supplier relational trust (BSRT), while information exchange is negatively associated with BUO (H4a). Support for the negative effect of BUO on BSRT is confirmed (β = –.44, p < .001, t = 11.53, effect size (f² ) = .30), while the negative association between buyer-supplier information exchange (BSIE) and BUO is also supported (β = –.11, p < .05, t = 2.54). However, regarding H_4b, we did not find support for the direct effect of BSIE on BSRT (β = .02, p > .05; see Table 5).

Table 5.

Structural Model Results, Effect Sizes (f² ) and Collinearity (VIF) (n = 444).

Criterion	R²	Predictors	Pathcoefficients	t-values#	f²	VIF
Buyer-supplier relational satisfaction	0.17	Buyer-supplier cooperation	0.41***	9.55	0.20	1.00
Buyer/agent opportunism	0.19	Buyer-supplier cooperation	-0.13**	2.56	0.02	1.33
		Buyer-supplier relational satisfaction	-0.23***	4.71	0.05	1.25
		Information exchange	-0.11**	2.54	0.01	1.23
		Power asymmetry	0.22***	5.39	0.06	1.02
		Relationship duration	0.05	1.24	0.00	1.03
		Buyer-supplier relational satisfaction xPower asymmetry	0.09**	2.52	0.01	1.01
		Buyer-supplier relational satisfaction xRelationship duration	0.07*	1.86	0.01	1.04
Buyer-supplier relational trust	0.48	Buyer-supplier cooperation	0.24***	5.60	0.08	1.38
		Buyer/agent opportunism	-0.44***	11.53	0.30	1.24
		Buyer-supplier relational satisfaction	0.23***	5.13	0.08	1.35
		Information exchange	0.02	0.48	0.00	1.25
		Power asymmetry	-0.01	0.16	0.00	1.11
		Relationship duration	-0.03	0.81	0.00	1.08
		Sales volume	-0.06^a	1.53	0.01	1.21
		Gender	0.04	1.10	0.00	1.12
		Membership of cooperative	-0.03	0.81	0.00	1.06
		Size of farm enterprise	-0.03	0.73	0.00	1.31
		Buyer/agent opportunism xRelationship duration	-0.05^a	1.42	0.00	1.09
		Buyer-supplier relational satisfaction xPower asymmetry	0.05	1.19	0.00	1.03
		Buyer-supplier relational satisfaction xRelationship duration	-0.06^a	1.40	0.01	1.09

Note: # Based on 10000 bootstrapping samples ***p <0.001, **p < 0.05 (two-tailed); *p < 0.05, ^a p < 0.10 (one-tailed).

As shown in Table 5, the moderating role of power asymmetry between BSRS and BUO and the moderating role of relationship duration between BSRS and BUO were also tested. Results showed that power asymmetry significantly moderates the link between BSRS and BUO (β = .09, p < .05, t = 2.52, two-tailed). Relationship duration was also found to be a significant moderator between the link of BSRS and BUO (β = .07, p < .05, t = 1.86, one-tailed). Further moderating effects were tested. The link between BUO and BSRT was found to be moderated by relationship duration (β = –.05, p < .10, t = 1.42, one-tailed), while the link between BSRS and BSRT was also found to be moderated by relationship duration (β = –.06, p < .10, t = 1.40, one-tailed). We also hypothesized that the effect of information exchange on relational trust is mediated by buyer opportunism (H₅). Thus, we examined some unique indirect effects (see Table 6). For example, the results show that buyer opportunism mediates the effect of information exchange on relational trust, providing support for H₅. Moreover, the effect of power asymmetry on relational trust was also found to be mediated by buyer opportunism, and the effect of cooperation in reducing perceptions of buyer opportunism was found to be mediated by relational satisfaction.

Table 6.

Unique Indirect Effects (n = 444).

Mediation relationship	Indirect effect	t-values#
Buyer-supplier cooperation → Buyer-supplier relational satisfaction → Buyer/agent opportunism	0.09***	4.38
Buyer-supplier cooperation → Buyer/agent opportunism → Buyer-supplier relational trust	0.06*	2.55
Buyer-supplier relational satisfaction → Buyer/agent opportunism → Buyer-supplier relational trust	0.10***	4.34
Information exchange → Buyer/agent opportunism → Buyer-supplier relational trust	0.05*	2.48
Power asymmetry→ Buyer/agent opportunism → Buyer-supplier relational trust	0.09***	4.63
Buyer-supplier cooperation → Buyer-supplier relational satisfaction → Buyer-supplier relational trust	0.09***	4.54

Note: # Based on 1000 bootstrapping samples ***p < 0.001, **p < 0.01, *p < 0.05 (two-tailed), mediator variable shown between arrows and indirect effects shows absolute values without sign.

The effects of the control variables, gender, size of the farm, and membership of cooperative on relational trust were insignificant (p > .05) while sales volume had a weak effect (β = -.06, t = 1.53, p < .10) (see Table 5). We conducted a multigroup analysis as a post-hoc evaluation to investigate differences between men and women cocoa suppliers. Table 7 shows the composite reliabilities and average variance extracted for the subsamples of women versus men-owned/managed farms. All the variables for the subsamples showed high reliability and average variance extracted values. However, the composite reliability value of information exchange showed differences between the two subsamples and hence not invariant. The multigroup analysis showed significant differences between men and women cocoa suppliers (see Table 8). The effect of information exchange on buyer opportunism was found to be significantly higher for men than for women (support for H₆), while the effect of buyer opportunism on relational trust was significantly greater for women than men (support for H₇).

Table 7.

Composite Reliability and Average Variance Extracted.

Construct	Composite reliability		t-value#Women vs.Men farm owners/managers	Average variance extracted		t-value#Women vs.Men farm owners/managers
Construct	Women farm owners/managers (n = 163)	Men farm owners/managers(n = 281)	t-value#Women vs.Men farm owners/managers	Women farm owners/managers(n = 163)	Men farm owners/managers(n = 281)	t-value#Women vs.Men farm owners/managers
Buyer-supplier cooperation	0.86	0.87	0.612	0.67	0.70	0.608
Information exchange	0.93	0.85	3.211**	0.81	0.65	3.672***
Buyer opportunism	0.97	0.97	0.759	0.82	0.81	0.770
Power asymmetry	0.87	0.90	0.411	0.70	0.76	0.818
Buyer-supplier relational satisfaction	0.95	0.96	0.456	0.80	0.82	0.458
Buyer-supplier relational trust	0.97	0.97	0.160	0.81	0.81	0.164

Note: # Based on 1000 bootstrapping samples ***p < 0.001, **p < 0.01 (two-tailed).

Table 8.

Structural Model Results and t-Statistic for Multigroup Analysis.

Criterion	Predictors	Women farm owners/managers(n = 163)		Men farm owners/managers(n = 281)		β1- β2	t-value
Criterion	Predictors	Pathcoefficient (β1)	t-value	Path coefficient (β2)	t-value	β1- β2	t-value
Buyer-supplier relational satisfaction	Buyer-supplier cooperation	0.32***	4.097	0.45***	9.337	0.13	1.550
Buyer/agent opportunism	Buyer-supplier cooperation	-0.20*	2.364	-0.09	1.585	0.11	1.030
	Buyer-supplier relational satisfaction	-0.22**	2.566	-0.22***	3.623	0.00	0.016
	Information exchange	0.03	0.399	-0.21***	4.084	0.24**	2.599
	Power asymmetry	0.22**	3.218	0.21***	4.600	0.01	0.047
	Relationship duration	0.02	0.287	0.07	1.417	0.05	0.560
	Buyer-supplier relational satisfaction xPower asymmetry	0.10	1.491	0.09	1.941	0.01	0.140
	Buyer-supplier relational satisfaction xRelationship duration	0.11	1.406	0.05	1.209	0.06	0.728
Buyer-supplier relational trust	Buyer-supplier cooperation	0.21**	3.024	0.25***	4.325	0.04	0.417
	Buyer/agent opportunism	-0.55***	8.689	-0.37***	7.426	0.18*	2.156
	Buyer-supplier relational satisfaction	0.17*	2.471	0.26***	4.519	0.09	0.986
	Information exchange	0.07	1.123	0.01	0.249	0.06	0.689
	Power asymmetry	0.01	0.195	-0.01	0.221	0.02	0.294
	Relationship duration	0.02	0.380	-0.06	1.376	0.08	1.139
	Sales volume	-0.04	0.637	-0.07	1.675	0.03	0.386
	Membership of cooperative	-0.06	1.075	-0.02	0.348	0.04	0.593
	Size of farm enterprise	-0.09	1.297	0.02	0.354	0.11	1.273
	Buyer/agent opportunism xRelationship duration	-0.04	0.776	-0.05	1.223	0.01	0.202
	Buyer-supplier relational satisfaction xPower asymmetry	0.02	0.223	0.04	0.980	0.02	0.334
	Buyer-supplier relational satisfaction xRelationship duration	0.02	0.311	-0.08	1.561	0.10	1.178

Notes: t-values are based on 1000 bootstrapping samples ***Significant at p < 0.001 level **Significant at p < 0.01 *Significant at p < 0.05 (two-tailed test).

Discussion

The paper sought to investigate trust-building antecedents in supply markets characterised by numerous smallholder suppliers in a developing economy. Some findings in this study predict trust building in SHACS supply markets. Buyer-supplier relational trust is significantly influenced by cooperation, opportunism, and relational satisfaction. The influence of buyer opportunism on relational trust has the highest effect (f² = .30), implying that unethical behaviour in the form of opportunism is one of the most significant factors inhibiting trustworthiness between SHACS and buyers. Opportunism has been identified as one of the key institutional challenges that mitigates sustainability (Hahn and Gold 2014; Kistruck et al. 2011; Kistruck et al. 2013). Many lead firms are looking to engage with SHACS suppliers; however, in most cases, lead firms are rarely in direct trading relationships with SHACS. The relationships are mediated by one or more levels of trader or supplier (Vorley and Thorpe 2014).

Several questions arise. How can lead firms open their supply chains to SHACS? For those lead firms already dealing with SHACS, how can they sustain their relationships? In most cases, a clear business case exists when a value is generated for the lead firm, the trader and the SHACS. For the lead firm, the objective may be to secure supply when there are few alternatives (i.e., in terms of large commercial farms), as occurres in most commodity value chains (e.g., cocoa, cotton, coffee, and tea) where smallholder suppliers dominate. Supply risk is a major concern for managers who source globally (Vedel and Ellegaard 2013). Lead firms may also be concerned with brand image and reputation, especially in an era in which consumers are well informed about the integrity of ingredients used in the manufacture of food products, environmental consciousness, and corporate social responsibility.

The threat of opportunism seriously undermines efforts to integrate SHACS into the supply chains of lead firms (Multinational enterprises-MNEs and small and medium-sized enterprises-SMEs), at both the national and the global level. Besides, institutional voids emanating from weak markets and little legal enforcement create conditions for unethical behaviours (Amankwah-Amoah, Debrah, and Nuertey 2018). SHACS are also vulnerable to manipulation by government officials, companies (Jelsma et al. 2017), and their agents. The findings show that cooperation, relational satisfaction, and information exchange had significant negative effects on perceptions of buyer opportunism consistent with the literature. Based on the BOP context, prior research highlighted the role of cooperation. For example, in a social business joint venture, exclusive cooperation with local farmers – as suppliers for raw materials – was critical in the success of the venture (Hahn and Gold 2014). In the context of international buyer-supplier relationships, a meta-analysis by Leonidou et al. (2014) found support for a negative link between opportunism and outcome variables, such as cooperation, trust, and commitment.

The social system in which a lead firm operates is important in SHAC supply networks. The social system of the smallholder agro-commodity value chain is characterised by social norms and rules of engagement and the value system prevailing within the market, industry or business environment. Lead firms wishing to deal with SHACS need to learn the “language”. Therefore, sharing benefits and risks all along the chain are aims that can be supported by greater communication and transparency between chain actors (Vorley and Thorpe 2014). Transparency must extend to the buying and sourcing companies, with top management that is well versed in transparency and governance issues. In the context of manufacturers and their distributors, Zhou et al. (2015) highlighted the role of relational norms and collaborative activities in reducing opportunism in marketing channels. Perceptions of opportunism in a SHACSM is manageable through cooperative relationships.

Eckerd and Hill (2012) found buyer-supplier information exchange significantly reduced perceived unethical behaviour on the part of the buying firm, while it increased perceived buying firm commitment. Unethical behaviour by the buying firm was found to reduce commitment significantly (Eckerd and Hill 2012). The development of cooperative behaviours in long-term relationships promotes greater benefits (Graca, Barry, and Doney 2015; Kim and Choi 2015; Lambe, Wittmann, and Spekman 2001) and value chain performance improvement. The exchange of information is the “glue” that binds parties together in exchange relationships. Access by SHACS to information (e.g., market) and upgrading opportunities by lead firms or in collaboration with government and non-governmental institutions can help in alleviating poverty and the many challenges in a SHACSM.

Theoretical Contributions and Implications

This paper makes several theoretical, managerial, and policy contributions to the literature. First, the conceptual model highlighted an important issue in the context of the smallholder agro-commodity supply market (SHACSM) that has been mostly unexplored. Trust-building is a critical issue in the SHACSM if trustworthy supply relationships are to be realised, and if the smallholder agro-commodity suppliers are to be successfully integrated into value-adding initiatives and global supply chains. Second, the study proposed and confirmed some established associations between relationship variables (e.g., opportunism and trust) and highlighted some unique associations (e.g., mediation and moderation effects). The theoretical contributions concerning the moderation effects are: for short-term transactional exchanges, relational satisfaction enhances trust formation. This is in line with social exchange postulations where repeated satisfactory exchanges enhance trust formation. Personal relationships between members of the buying and selling firms help to build trust, which in turn helps to reduce risk (Håkansson and Östberg 1975).

The distinction between short-term and long-term exchange situations contributes to theory. The term “temporal issues” refers to the role that time plays in studying and understanding phenomena or variables of interest (Fisher, Ragsdale and Fisher 2019). Time is critical regarding the way psychological phenomena manifest and unfold (Ancona et al. 2001; Fisher, Ragsdale and Fisher 2019). Clarity on temporal processes in macromarketing research could help provide better understanding of why certain phenomena unfold in a particular way. In the emerging markets context of highly fragmented small-scale suppliers, buyers’ purchasing agents must be trustworthy to build long-term relationships with suppliers. These sellers occupy a vulnerable position in the transaction exchange and are especially vulnerable to performance risk and opportunism (Dadzie, Dadzie, and Williams 2018). The effect of opportunism in reducing trust is more pronounced in long-term relational exchanges. This finding contributes to the opportunism-trust link (Crosno and Dahlstrom 2010). “Positive outcomes over time produce relational exchange norms” (Lambe, Wittmann, and Spekman 2001, p. 11) that are expected to govern the relationship and reduce perceptions of opportunism. We also find fewer perceptions of opportunism in satisfying relationships with low power asymmetry. This is logical because the perception of opportunism is high in those exchanges that are characterised by high power asymmetry and unsatisfactory social or economic outcomes (Blau 1968; Homans 1958). An imbalance in power in long-term interfirm relationships can create opportunities to act opportunistically and exercise coercion (Ireland and Webb 2007). Power asymmetry inhibits supply chain innovation by small suppliers as power imbalance can result in the use of coercive power by the more dominant buyer. Small suppliers have to devote more resources to ensuring the maintenance of contracts with powerful buyers (Matanda, Ndubisi, and Jie 2016).

The misuse of power can lead to mistrust. This study highlights the mediating role of opportunism between power asymmetry and relational trust. In the research context, preliminary qualitative interviews show that day-to-day interactions and cooperation are between purchasing officers and individual small-scale farmers. Collectively, small farmers can cooperate to mitigate the power of opportunism of the LBCs and their agents. Meier zu Selhausen (2016) found that women’s active participation in agricultural-marketing cooperatives and collective action enabled them to mitigate socio-economic constraints. The implication is that small-scale farmers’ participation in agricultural marketing cooperatives can yield enormous bargaining power and collective action to reduce opportunism.

We also find that the impact of satisfaction in reducing perceptions of opportunism is more pronounced in short-term transactional exchanges than in long-term relationships. This finding contradicts social exchange theory (Blau 1968; Homans 1958) which postulates that in long-term relational exchanges positive outcomes over time increase trust and commitment (Lambe, Wittmann, and Spekman 2001; Morgan and Hunt 1994). High levels of relational exchange features are based on each partner’s historical and long-term view of the exchange relationship (Glavee-Geo and Engelseth 2018; Lambe, Wittmann, and Spekman 2001). Most smallholder cocoa growers have a long-term relationship with their exchange partners. However, the outcomes of such relationships have fallen below expectations regarding economic benefits. Cocoa farmers are mandated to sell cocoa to only designated licensed buying companies at a minimum guaranteed price set by the Ghana Cocoa Board, the state organization that regulates the cocoa industry.

Long-term relationships are not without short-term transactional exchange— comparisons regarding long and short-terms show that satisfaction enhances trust formation in short-term relationships. Satisfaction reduces perceptions of opportunism in short-term relationships compared to the overall long-term perspective. The theoretical and research contribution suggest that the impact of relationship variables such as satisfaction on trust or opportunism is dependent on the duration of the relationship. Modelling of relationship variables should not be done in isolation without considering how long exchange relationship partners have been dealing with each other. The impact of certain predictors on trust systematically varies over time (Korsgaard et al. 2018; Lewicki, Tomlinson and Gillespie 2006).

The study also shows that the effect of information exchange on relational trust is mediated by buyer opportunism. Information increases trust. However, lack of information enhances perceptions of opportunism and mistrust. Information exchange enhances trustworthiness (Anderson and Weitz 1989; Morgan and Hunt 1994). Information exchange is an important antecedent of opportunism. The literature (e.g. Viitaharju and Lähdesmäki 2012) argues that if exchange partners are unaware of the antecedents of trust, of which communication is one, this may create a sense of mistrust and hinder the development of the relationship due to power asymmetry. In addition, a firm, or its agent, that engages in opportunistic behaviour may signal suspicion, generate ill will and incite resentment in their partner, leading to a lower level of commitment in the relationship (Mysen, Svensson and Payan 2011). The present study also contributes to the business relationship and macromarketing literature by showing empirical support for the moderating role of gender in opportunism-trust relationships. These and other issues discussed earlier have implications for public policy and macromarketing.

Public Policy, Managerial Implications and Macromarketing

The first policy implications is, if poverty reduction is to be sustainable, the key is long-term orientation. Although ethical issues dominate the smallholder agro-commodity supply market (SHACSM), we find that satisfactory buyer-supplier relationships are important in reducing perceptions of opportunism, especially when intermediaries are involved. The buyer opportunism–relational satisfaction link is contingent on the history of the relationship: in short relationships, relational satisfaction has a stronger negative effect on perceptions of buyer opportunism. This implies that sourcing companies’ top management must be mindful of how this perception should be managed if the inclusion of the SHACS in the value chain for critical raw materials is to reduce supply risk. In managing these perceptions, focus should be on businesses owned and operated/managed by women due to their developmental impact on households and the local communities. This is in line with macromarketing practice and goals (Nason, 1988; Peterson 2013; Peterson and Zehra 2018; Sheth 2011).

Second, power asymmetry between lead firms and smallholder suppliers enhance perceptions of opportunism, bringing to light the need to manage this perception for improved relational satisfaction between the parties. This is important because smallholder farmers have low bargaining power in such transactions and are disadvantaged. The preference for short transactional exchanges in the research context can be explained by the nature of the product being exchanged. Cocoa is a commodity which relates well to transactional exchanges. However, some cocoa producers (about 40% of the sample) have been in a stable long-term exchange relationship of more than five years. Besides, more than 80% of the smallholder cocoa growers sampled are over 40 years. Due to the substantial imbalance in economic development between urban and rural areas in most developing countries, many young people migrate from rural areas to urban centers to improve their living standards (Dadzie, Akaah, and Dunson 1989).

Third, smallholder cocoa growers are mostly elderly because of the migration of young and able-bodied men to cities and towns. In most developing countries, the rural-urban movement has led to low agricultural productivity (Dadzie, Akaah, and Dunson 1989) and shortages that are threatening sustainability (Fisk 2006). The public policy implication regarding the sustainability of the industry suggests the need for more proactive efforts by the government and non-governmental agencies to help formulate and implement policies to encourage the young to go into agricultural production. This is critical since cocoa is a valuable export commodity, which forms the backbone of the country’s economy. Furthermore, illegal, unauthorised, undocumented, irregular migration (terms synonymously used - Dauvergne 2017) is of current concern, and the mass movement of people with unverified legal status into developed Western nations poses challenges to social cohesion. The macromarketing implication here is that policies in developing countries that ensure consumer well-being and quality of life (Sandikci et al. 2016) through work opportunities, especially in agriculture, technology and services can reduce the urban-rural drift and global illegal migration.

Fourth, when trust does develop in power-dependent relationships, some form of third-party enforcement may still be necessary to ensure against the worst abuses or exploitation of the relationship, even when the basis of trust is the ongoing dyadic interaction (Cook, Hardin, and Levi 2005, p. 4). This is where third parties, such as government and non-business institutions and organisations, have a role to play. In most cases, businesses do not know the smallholder agro-commodity market (SHACSM) well, compared to non-business actors, such as non-governmental organisations and government institutions (Hahn and Gold 2014; Prahalad and Hart 2002). Good working partnerships between businesses, non-business actors and SHACS can help in more efficient value chain governance and integrity in these markets.

The literature (e.g., Poppo and Zenger 2002) points to the idea of combining formal and informal governance mechanisms as “a plural form of governance.” However, research suggests that informal governance mechanisms play a significant role in mitigating opportunism (Hahn and Gold 2014). This is because of weak institutional structures, or even the lack thereof, to support contract enforcement at the BOP (2014; Rivera-Santos, Rufín, and Kolk 2012). Thus, relational governance, with key relational norm dimensions of cooperation, information exchange, trust, and economic and social satisfaction, is key to the sustainability and governance of the SHACSM.

Fifth, given the dependence of smallholder agro-commodity suppliers (SHACS) on the more powerful and often better-resourced buyers or their agents, demonstrating trustworthiness is important in the long-term orientation of the SHACSM. Buyers can take several actions to enhance sellers’ perceptions of buyer integrity and ability. Dadzie, Dadzie, and Williams (2018) suggest that buyers could make efforts to share records and accounts associated with the produce weighing and purchasing transactions. Such an action is increasingly becoming a critical requirement as emerging markets liberalise their agro-commodity supply markets and exporting firms compete for market share in local export produce such as cocoa and coffee (Dadzie, Dadzie, and Williams 2018, p.137). Moreover, lead firms can train and align the objectives, incentives, and motivations of their sourcing managers, frontline staff and intermediaries who deal directly with SHACS as “accredited ethical agents” or “value chain connectors” (Buxton and Vorley 2012; Vorley and Thorpe 2014). These ethical agents can build trustworthy and satisfactory relationships between SHACS and the lead firms. In addition, due to potential agency problems (Eisenhardt 1989), lead firms need to structure appropriate governance and monitoring systems to control opportunistic behaviour in their intermediaries and agents.

Sixth, the study reports significant differences in perceptions of men and women regarding the consequent effect of opportunism on trust. The attention to gender issues within the cocoa industry of Ghana was earlier noted by Mikell (1992). Mikell reports the detrimental effects of government policy (e.g. price control and its effect on household income) on women and children in cocoa growing communities. The role of women in agricultural marketing systems cannot be underemphasised. Women produce over 50 percent of the world’s food and comprise about 43 percent of the farm labour force, both globally and in developing countries (Akter et al. 2017). Additionally, women invest up to ten times more of their earnings than men do in their family’s well-being, including child health, education, and nutrition (Akter et al. 2017; Duflo 2012; Maertens and Verhofstadt 2013). The agricultural sectors of most developing countries (especially the agro-commodity export subsector) face a sustainability crisis, including a range of social, environmental and economic challenges. The public policy implication is that there is a need for “crafting” transformative structural solutions and cooperation to support women’s smallholder farm businesses as a critical step to creating sustainable women enterprises. Businesses can be a positive influence in addressing problems for societies and local communities (Peterson 2013).

Donor agencies, local governments, and NGOs are increasingly targeting women as priority clients and strengthening their investments to empower women and reduce the inequity between sexes (Gates 2014). The Sustainable Development Goals (SDGs) of “Achieving gender equality and empowering all women and girls” (SDG#5) (United Nations 2017) is consistent with the ideals of macromarketing (Peterson 2013; Peterson and Zehra 2018).

Conclusion

This study examined the perception of agro-commodity (cocoa) suppliers in a dyadic relationship. Further research should include viewpoints from both sides of the dyad to provide more insights regarding the smallholder agro-commodity market. By providing empirical insights from the cocoa value chain, this study encourages more research in other contexts, commodities (e.g., coffee, tea, or cotton) and value chains (e.g., textiles, fruits, or vegetables) in emerging and developing countries.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Richard Glavee-Geo

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