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This study aims to study research on franchise chain performance that has focused on franchisors’ efforts to align their interests with those of franchisees to address partner uncertainty. In contrast, the question of what a franchisor should do to address another type of uncertainty and task uncertainty remains understudied. The authors suggest a franchisor’s coordination as a key means of alleviating task uncertainty and ongoing support and plural form as two mechanisms of coordination. The authors also posit that aligned interests between the franchisor and the franchisee improve, whereas one-sided interest impedes, chain performance. Furthermore, providing greater ongoing support or deploying plural form amplifies the positive effect of aligned interests on chain performance.

The authors relied on secondary data to test the hypotheses. The authors collected data for analysis from Bond’s franchisee guide and Nation’s Restaurant News restaurant database. They also tested the framework by analyzing 17-year, panel data of 71 restaurant chains operating in the USA and Canada using system generalized method of moments.

Results show that aligning interests does improve chain performance, but that the positive effect is amplified when aligned interests are matched with a chain’s provision of ongoing support or use of plural form.

The authors explicate why it is not enough to address the misaligned interests or lack of coordination alone; a chain manager needs to address both of these problems together. In addition, the authors explicate how two franchisee coordination mechanisms – ongoing support and plural form – help a chain augment the beneficial effect of aligning interests on chain performance. Without solving the twin problems of misaligned interests and coordination simultaneously, a chain is unlikely to achieve its full performance potential.

This paper aims to study the antecedents of Internet of Things (IoT) adoption among farmers and determine how trust in the technology influences its adoption when mediated by perceived value and risk. Through the conceptualization of trust and perceived risk, the authors factor in farmers’ perceptions of agricultural technology providers and discuss different forms of perceived value, spanning economic, green and epistemic value.

This paper develops a distinctive research design, drawing on elements of the value-based adoption and technology acceptance models. By linking different elements of perceived value with IoT technology, the authors also apply the service-dominant logic to this study. They study how trust affects perceived value and risk and then determine how perceived value and risk, in turn, affect IoT adoption. The authors test the hypotheses by developing a structural equation model to analyze the results of a survey, wherein 492 farmers from Iowa, the USA, participated.

The results show a positive relationship between trust and perceived value and a negative relationship between trust and perceived risk. Perceived value had a positive impact on IoT adoption, whereas perceived risk had a negative impact on IoT adoption.

The research findings on trust and perceived value and risk are timely and relevant for business-to-business (B2B) marketing practitioners and agricultural stakeholders, especially in an era where farmers are expressing growing concerns about data handling risk posed by IoT technology adoption.

The research findings signal a transition in focus from the goods-dominant logic to the service-dominant logic in agriculture, whereby farmers are drawn to IoT technology because of perceived economic, green and epistemic value and as a result, can differentiate themselves on how well they deploy operant resources. This paper not only provides a unique conceptualization of perceived value but also pave the way for a richer conceptualization of IoT core functions that enable farmers to fulfill green and epistemic goals. This is the first B2B marketing paper discussing the antecedents of IoT adoption in agriculture, such as farmers’ perceptions of both monetary and non-monetary forms of value and perceived data handling risk.