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Soil quality is in decline in many parts of the world, in part due to the intensification of agricultural practices. Whilst economic instruments and regulations can help incentivise uptake of more sustainable soil management practices, they rarely motivate long-term behavior change when used alone. There has been increasing attention towards the complex social factors that affect uptake of sustainable soil management practices. To understand why some communities try these practices whilst others do not, we undertook a narrative review to understand how social capital influences adoption in developed nations. We found that the four components of social capital – trust, norms, connectedness and power – can all influence the decision of farmers to change their soil management. Specifically, information flows more effectively across trusted, diverse networks where social norms exist to encourage innovation. Uptake is more limited in homogenous, close-knit farming communities that do not have many links with non-farmers and where there is a strong social norm to adhere to the status quo. Power can enhance or inhibit uptake depending on its characteristics. Future research, policy and practice should consider whether a lack of social capital could hinder uptake of new practices and, if so, which aspects of social capital could be developed to increase adoption of sustainable soil management practices. Enabling diverse, collaborative groups (including farmers, advisers and government officials) to work constructively together could help build social capital, where they can co-define, -develop and -enact measures to sustainably manage soils.

This paper aims to recall the attention on a key challenge for customer relationship management related to the role of human agents in the management of the “switch point” for ensuring the effectiveness and efficiency in a customer-machine conversation.

This study contributes to the discussion about the firms’ approach to artificial intelligence (AI) in frontline interactions under the conceptual umbrella provided by knowledge management studies.

This paper provides a theoretical model for clarifying the role of human intelligence (HI) in AI-based frontline interactions by highlighting the relevance of the actors’ subjectivity in the dynamics and perceptions of customer-machine conversations.

An AI-HI complementarity matrix is proposed in spite of the still dominant replacement view.

To understand how narratives used by entrepreneurial support organizations (ESOs) in Detroit's growing entrepreneurial ecosystem shape transitional entrepreneurs' social reality. We offer theoretical and practical insights to elicit critical support, formulate policies and programs and guide ongoing empirical examination of transitional entrepreneurship.

We adopt a multi-case study approach, looking at two ESOs in Detroit: one focused on promoting high-growth entrepreneurship and securing financial capital for technology entrepreneurs, the other focused on promoting everyday entrepreneurship (especially among underserved communities) and amassing a more diverse array of resources. We conduct a thematic analysis of organizational texts and interview data with ESO leaders.

ESO narratives shape Detroit's transitional entrepreneurs by constructing entrepreneurs' social identity, orienting them to the ecosystem and envisioning a collective future in which transitional entrepreneurs are key.

This study offers insight into the definition of transitional entrepreneurs by extending existing conceptions by highlighting the role of institutional actors, like ESOs, and the narratives they adopt in shaping opportunities and challenges for transitional entrepreneurs. Moreover, we push the boundaries of transitional entrepreneurship, including technology start-up entrepreneurs in the definition and call attention to the role of transitional entrepreneurs in post-industrial cities by showcasing their role in community and urban development.

Disruptive technologies are accelerating global growth. Artificial intelligence (AI) has the potential to transform the idea of delivering value to end users. On the other hand, the growth of Industry 5.0 has given rise to the concept of humanizing technology, and AI is a promising technology with the potential to contribute to business success. Nevertheless, the idea of value creation in the field of AI is novel, so it is necessary to define the meaning of value by understanding the context of AI applicability in different environments and industries. In this chapter, the author uses the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) procedure to conduct an SLR that provides interesting insights into the focus, industries, and methodologies and approaches used in existing research. Following the initial literature review on the state of the art of AI and value creation, the author also offers a reflection on the strategic implications of AI in the field of marketing, postulating a macrovalue creation framework that addresses the existence of implications on three different levels: emerging markets, Sustainable Development Goals, and adoption issues. Therefore, this chapter examines the value creation perspectives of AI to understand the current research focus and future directions.

The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and implementation.

The research employed two experimental designs and one pilot study to investigate the ethical and moral implications of different levels of AI implementation in the hospitality industry, the intersection of self-congruency and ethical considerations when AI replaces human service providers and the impact of psychological distance associated with AI on individuals' ethical and moral considerations. These research methods included surveys and experimental manipulations to gather and analyze relevant data.

Findings provide valuable insights into the ethical and moral dimensions of AI implementation, the influence of self-congruency on ethical considerations and the role of psychological distance in individuals’ ethical evaluations. They contribute to the development of guidelines and practices for the responsible and ethical implementation of AI in various industries, including the hospitality sector.

The study highlights the importance of exercising rigorous ethical-moral AI hiring and implementation practices to ensure AI principles and enforcement operations in the restaurant industry. It provides practitioners with useful insights into how AI-robotization can improve ethical and moral standards.

The study contributes to the literature by providing insights into the ethical and moral implications of AI service robots in the hospitality industry. Additionally, the study explores the relationship between psychological distance and acceptance of AI-intervened service, which has not been extensively studied in the literature.

The impact of frontline robots (FLRs) on customer orientation perceptions remains unclear. This is remarkable because customers may associate FLRs with standardization and cost-cutting, such that they may not fit firms that aim to be customer oriented.

In four experiments, data are collected from customers interacting with frontline employees (FLEs) and FLRs in different settings.

FLEs are perceived as more customer-oriented than FLRs due to higher competence and warmth evaluations. A relational interaction style attenuates the difference in perceived competence between FLRs and FLEs. These agents are also perceived as more similar in competence and warmth when FLRs participate in the customer journey's information and negotiation stages. Switching from FLE to FLR in the journey harms FLR evaluations.

The authors recommend firms to place FLRs only in the negotiation stage or in both the information and negotiation stages of the customer journey. Still then customers should not transition from employees to robots (vice versa does no harm). Firms should ensure that FLRs utilize a relational style when interacting with customers for optimal effects.

The authors bridge the FLR and sales/marketing literature by drawing on social cognition theory. The authors also identify the product categories for which customers are willing to negotiate with an FLR. Broadly speaking, this study’s findings underline that customers perceive robots as having agency (i.e. the mental capacity for acting with intentionality) and, just as humans, can be customer-oriented.

Technology-enabled business-to-business (B2B) services contribute the largest share to GDP growth and are fundamental for an economy’s value creation. This article aims to identify key service- and digital technology-driven B2B innovation modes and proposes a research agenda for further exploration.

This conceptual paper adopts a techno-demarcation view on service innovation, encompassing three core dimensions: service offering (the service product, or the “what”), service process (the “how”) and service ecosystem (the “who/for whom”). It delineates the implications of three digital technologies – the internet-of-things (IoT), intelligent automation (IA) and digital platforms – for service innovation across these core dimensions in B2B markets.

Digital technology has immense potential ramifications for value creation by reshaping all three core dimensions of service innovation. Specifically, IoT can transform physical resources into reconfigurable service products, IA can augment and automate a rapidly expanding array of service processes, while digital platforms provide the technical and organizational infrastructure for the integration of resources and stakeholders within service ecosystems.

This study suggests an agenda with six themes for further research, each linked to one or more of the three service innovation dimensions. They are (1) new recurring revenue models, (2) service innovation in the metaverse, (3) scaling up service innovations, (4) ecosystem innovations, (5) power dependency and lock-in effects and (6) security and responsibility in digital domains.

This paper examines the relationship between marketing automation emergence and the marketers' use of heuristics in their decision-making processes. Heuristics play a role for the integration of human decision-making models and automation in augmentation processes, particularly in marketing where automation is widespread.

This study analyzes qualitative data about the impact of marketing automation on the scope of heuristics in decision-making models, and it is based on evidence collected from interviews with twenty-two experienced marketers.

Marketers make extensive use of heuristics to manage their tasks. While the adoption of new automatic marketing tools modify the task environment and field of use of traditional decision-making models, the adoption of heuristics rules with a different scope is essential to defining inputs, interpreting/evaluating outputs and control the marketing automation system.

The paper makes a contribution to research on the relationship between marketing automation and decision-making models. In particular, it proposes the results of in-depth interviews with senior decision makers to assess the impact of marketing automation on the scope of heuristics as decision-making models adopted by marketers.

Companies utilize increasingly capable Artificial Intelligence (AI) technologies to deliver modern services across a range of consumer service industries. AI autonomy, however, sparks skepticism among consumers leading to a decrease in their willingness to adopt AI services. This raises the question as to whether consumer trust in companies can overcome consumer reluctance in their decisions to adopt high (vs low) autonomy AI services.

Using a representative survey (N = 503 consumers corresponding to N = 3,690 observations), this article investigated the link between consumer trust in a company and consumers' intentions to adopt high (vs low) autonomy AI services from the company across 23 consumer service companies accounting for six distinct service industries.

The results confirm a significant and positive relationship between consumer trust in a company and consumers' intentions to adopt AI services from the same company. AI autonomy, however, moderates this relationship, such that high (vs low) AI autonomy weakens the positive link between trust in a company and AI service adoption. This finding replicates across all 23 companies and the associated six industries and is robust to the inclusion of several theoretically important control variables.

The current research contributes to the recent stream of AI research by drawing attention to the interplay between trust in companies and adoption of high autonomy AI services, with implications for the successful deployment and marketing of AI services.

This paper aims to identify the antecedents and postcedents of customer satisfaction, including utilitarian, social and emotional factors, in a fair trade (FT) coffee consumption context.

This paper is based on a broad range of 177 consumers of FT coffee in Spain, the data analysis used structural equation modeling (SEM) with SPSS/AMOS 26.0 software.

This paper supports that both customer social value and quality affect perceived value (PV). PV in turn has effects on customer satisfaction and the latter influences loyalty. Conversely, both customer emotional value and customer expectations were not confirmed as antecedents of PV.

The consumer satisfaction analysis conducted differs substantially from those of conventionally traded coffee, as social and emotional factors were considered along with utilitarian factors.

Practitioners, retailers and relevant institutions should design strategies to manage efficiently channel efforts to improve the consumer satisfaction and its loyalty.

This paper contributes to a substantial improvement in the understanding of consumer satisfaction and its consequences, in FT coffee consumption contexts. A new integrated theoretical model on customer satisfaction has been provided, which includes social and emotional perception factors, along with cognitive perception (quality and expectations) factors.

研究旨在確認在公平貿易咖啡消費的課題上，顧客滿意的誘因及其後因，這包括實用的因素，社會的因素和情感的因素。

研究之數據廣泛來自在西班牙177名公平貿易咖啡消費者; 分析則以結構方程模型，並以SPSS Amos 26軟件來進行。

研究結果證實，顧客社會價值和質量是會影響認知價值的;認知價值繼而影響顧客滿意度，而顧客滿意度又進而影響他們的忠誠。相反的，顧客情緒價值或他們的期望、均未能證實是認知價值的先決條件。

本研究所進行的消費者滿意度分析，與其它以傳統方法銷售的咖啡之相關研究有很大的分別，這是因為本研究除了考慮實用的因素外，還納入了社會因素和情感因素。

從業人員、零售商和有關的機構應制訂適切的策略，以能有效地管理各個管道，來提升消費者的滿意度和忠誠。

本研究的貢獻在於它幫助我們在公平貿易咖啡消費的課題上，對消費者滿意及其效果有更深入的認識。研究亦提供了一個探討顧客滿意度的嶄新、綜合的理論模型，而這個理論模型，除了涵蓋知覺認知 (質量和期望) 的因素外，還納入了社會的和情感的知覺因素。