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The purpose of this paper is to identify requirements and tradeoffs on logistics services for enhanced circularity of materials and resources.

Based on multiple case study design and abductive reasoning, the study investigates 13 different product categories. The data were analyzed based on theoretical, a priori codes from the literature review. Inductive, emerging codes were added to the coding scheme during the analysis.

Requirements of logistics services to support slowing of resource flows are categorized with respect to initiator, location of the service, single or multiple actors, and transportation of parts, products and people. Moreover, the study identifies new logistics tradeoffs: material and people, knowledge and people, and information and knowledge. Transportation of product, people and parts can be reduced by increasing local knowledge and improve information sharing.

This review contributes to the understanding of the relationship between logistics services and enhancement of circularity by highlighting requirements on logistics services in the aftermarket supply chain that support slowing of resource flows. To enhance circularity, logistics services must extend the traditional material information flow with the flow of people and knowledge, respectively.

The categorization provides practitioners and researchers with an overview of requirements and tradeoffs on logistics services to enhance circularity of a particular circular cycle. The implications will provide an opportunity to address environmental impact of transportation and improve the utilization of scarce materials.

Variety of tradeoffs in logistics services can enhance slowing and hence circularity of scarce materials.

First, the authors illustrate how traditional tradeoffs in logistics such as flow of materials, resources and people need to be addressed to enhance circularity through slowing. Second, the authors identify two new tradeoffs in logistics services: knowledge flow and degree of customer involvement.

In this article, we reflect on how smart technology is transforming service research discourses about service innovation and value co-creation. We adopt the concept of technology smartness’ to refer to the ability of technology to sense, adapt and learn from interactions. Accordingly, we seek to address how smart technologies (i.e. cognitive and distributed technology) can be powerful resources, capable of innovating in relation to actors’ agency, the structure of the service ecosystem and value co-creation practices.

This conceptual article integrates evidence from the existing theories with illustrative examples to advance research on service innovation and value co-creation.

Through the performative utterances of new tech words, such as onlife and materiality, this article identifies the emergence of innovative forms of agency and structure. Onlife agency entails automated, relational and performative forms, which provide for new decision-making capabilities and expanded opportunities to co-create value. Phygital materiality pertains to new structural features, comprised of new resources and contexts that have distinctive intelligence, autonomy and performativity. The dialectic between onlife agency and phygital materiality (structure) lies in the agencement of smart tech–enabled value co-creation practices based on the notion of becoming that involves not only resources but also actors and contexts.

This paper proposes a novel conceptual framework that advances a tech-based ecology for service ecosystems, in which value co-creation is enacted by the smartness of technology, which emerges through systemic and performative intra-actions between actors (onlife agency), resources and contexts (phygital materiality and structure).

Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed for this purpose. However, analyzing GPR data is labour-intensive and repetitive. It may therefore be worthwhile to amplify this process by means of Machine Learning (ML). In this work, harnessing the ADR design science methodology, an Intelligence Amplification (IA) system is designed that uses ML for decision-making with respect to utility material type. It is driven by three novel classes of Convolutional Neural Networks (CNNs) trained for this purpose, which yield accuracies of 81.5% with outliers of 86%. The tool is grounded in the available literature on IA, ML and GPR and is embedded into a generic analysis process. Early validation activities confirm its business value.

Social enterprises (SEs) face tensions when combining financial and social missions, and this is particularly evident in the scaling process. Although extant research mainly focuses on SEs that integrate their social and financial missions, this study aims to unpack social impact scaling strategies in differentiated hybrid organizations (DHOs) through the case of African SEs.

The study entails an inductive multiple case study approach based on four case SEs: work integration social enterprises (WISEs) and fair trade producer social enterprises (FTPSEs) in Uganda and Kenya. A total of 24 semi-structured interviews were collected together with multiple secondary data sources and then coded and analyzed through the rigorous Gioia et al. (2013) methodology to build a theoretical model.

The results indicate that SEs, as differentiated hybrids, implement four types of social impact scaling strategies toward beneficiaries and benefits (penetration, bundling, spreading and diversification) and unveil different dual mission tensions generated by each scaling strategy. The study also shows mutually reinforcing mechanisms named cross-bracing actions, which are paradoxical actions connected to one another for navigating tensions and ensuring dual mission during scaling.

This study provides evidence of four strategies for scaling social impact, with associated challenges and response mechanisms based on the cross-bracing effect between social and financial missions. Thus, the research provides a clear framework (social impact scaling matrix) for investigating differentiation in hybridity at scaling and provides new directions on how SEs scale their impact, with implications for social entrepreneurship and dual mission management literature.

The model offers a practical tool for decision-makers in SEs, such as managers and social entrepreneurs, providing insights into what scaling pathways to implement (one or multiples) and, more importantly, the implications and possible solutions. Response mechanisms are also useful for tackling specific tensions, thereby contributing to addressing the challenges of vulnerable, marginalized and low-income individuals. The study also offers implications for policymakers, governments and other ecosystem actors such as nongovernmental organizations (NGOs) and social investors.

Despite the growing body of literature on scaling social impact, only a few studies have focused on differentiated hybrids, and no evidence has been provided on how they scale only the social impact (without considering commercial scaling). This study brings a new perspective to paradox theory and hybridity, showing paradoxes come into view at scaling, and documenting how from a differentiation approach to hybridity, DHOs also implemented cross-bracing actions, which are reinforcement mechanisms, thus suggesting connections and synergies among the actions in social and financial mission, where such knowledge is required to better comprehend how SEs can achieve a virtuous cycle of profits and reinvestments in social impact.

The current research aims to answer the following question: To what extent and under what conditions does hiring consultants to implement a customer relationship management (CRM) system produce performance gains for companies? To answer this question, this research delves into the critical interdependent roles of CRM consultant resources (CR) and user involvement (UI) in overcoming CRM’s technological and organizational implementation challenges.

A quantitative field study methodology was used to empirically test the research hypotheses. Cross-sectional data (N = 126) were collected from large client companies using CRM technology. Partial least squares-structural equation modeling was used to estimate the significance levels of the structural model.

The findings indicate that the extent to which CRM consultants improve CRM system quality (SQ) and, ultimately, firm performance, largely depends on UI, which acts as the key facilitating mechanism to cope with application complexity (APP) and requirements uncertainty (REQ).

This research probes into the largely unexplored interactions between CRM CR, UI, APP and REQ. Using these parameters, this model successfully predicts CRM SQ and firm performance.

Drawing on information processing theory, the linkage between buffering and bridging and the ability on the part of procurement to resolve demand–supply imbalances is investigated, as well as contexts in which these strategies may be particularly useful or detrimental. Buffering may be achieved through demand change or redundancy, while bridging may be achieved by the means of collaboration or monitoring.

This study employs a hierarchical regression analysis of a survey of 150 Finnish and Swedish procurement and sales and operations planning professionals, each responding from the perspective of their own area of supply responsibility.

Both the demand change and redundancy varieties of buffering are associated with procurement's ability to resolve demand–supply imbalances without delivery disruptions, but not with cost-efficient resolution. Bridging is associated with the cost-efficient resolution of imbalances: while collaboration offers benefits, monitoring seems to make things worse. Dynamism diminishes, while the co-management of procurement in S&OP improves procurement's ability to resolve demand–supply imbalances. The most potent strategy for tackling problematic contexts appears to be buffering via demand change.

The results highlight the importance of procurement in the S&OP process and suggest tactical measures that can be taken to resolve and reduce the effects of supply and demand imbalances.

The results contribute to the procurement and S&OP literature by increasing knowledge regarding the role and integration of procurement to the crucial process of balancing demand and supply operations.

The success of last-mile delivery is dependent on consumer acceptance of such services, yet little is known about unattended delivery experience. This paper's purpose is to provide empirically based understanding of customer experience dimensions in unattended home delivery.

Using an engaged scholarship approach, this field study investigated nine households that actively used an unattended delivery service for a period of six to nine months. Empirical data were collected primarily from in-depth interviews.

The study demonstrates that unattended delivery experience is a multidimensional construct that comprises consumers' cognitive, emotional, behavioral, sensorial, physical and social responses to the service. The empirical evidence provides rich descriptions of each customer experience dimension, and the research offers a framework and propositions on unattended delivery experience.

The results guide and support managers in assessing and developing delivery services using a consumer-centric approach to enhance customer experience.

This research is one of the first to address unattended delivery experience by providing a comprehensive, empirically grounded framework. The results provide a foundation for future investigations of last-mile delivery experience dimensions.

Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

Contemporary service and marketing research on value co-creation and value co-destruction assume a one-dimensional view on value, ranging from positive value co-creation, alignment and high value to negative value co-destruction, misalignment and low value. This limitation has recently led researchers to conceptually develop more dynamic spatial-temporal models of how value is formed during the interaction, e.g. in terms of different relationships between practice elements (procedures, understandings and engagements) both within and between actors in “value formation spaces”. However, much of this research awaits validation and is in need of more details. This study aims to address this limitation with the purpose of detailing how and why the mechanisms in such spaces are formed.

Two different and interlinked typologies were analytically derived from previous research and applied on ethnographically-inspired multi-perspective empirical data from a service combining health care and transport service ecosystems, using a combination of interviews, observations and service design methodologies. The design in combination with a practice theory perspective was used to articulate crucial aspects related to understanding the dynamics of value co-formation for elaborative and illustrative purposes.

The study contributes to service theory by conceptualizing as follows: a typology consisting of nine different configurations of practice elements (within and between such elements) and eight possible directions that value formation can take, suggesting a theory that explains value co-creation, value co-destruction and mixed cases.

Although the findings have been developed in a specific empirical context, they articulate a conceptualization applicable to many other service and marketing value co-formation settings.

The typologies are conceptual tools to be used in identifying and measuring the alignment/misalignment of practice elements in complex organizations. The empirical findings uncover service problems faced by disabled customers.

The suggested typologies can guide research and practitioners in understanding and analysing value co-formation mechanisms in complex service settings.

In the age of the Fourth Industrial Revolution, Industry 4.0 can increase the productivity and competitiveness of companies in the international marketplace. The purpose of this article is to investigate the drivers for and outcomes of the adoption of Industry 4.0 technologies in the case of a food processing company located in Italy.

The present work adopted a case study approach by investigating an Italian food processing company to investigate the drivers, challenges and outcomes of Industry 4.0 adoption in the agri-food sector.

This research highlighted drivers and challenges related to the adoption of different Industry 4.0 technologies. Secondly, it underlined the impacts of Industry 4.0 in terms of firm performance, operations management, human resource management and strategy.

Industry 4.0 technologies remain underexplored from the strategic perspective in the agri-food sector. This article provides preliminary evidence on the digital transformation of food processing companies, with a focus on Industry 4.0. Practical implications for managers, CEOs and entrepreneurs are discussed.