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This study aims to explore how sustainable business models (SBM) can be developed within agri-innovation systems (AIS) and emphasize an integration of the two with a systemic understanding for reducing food loss and value loss in postharvest agri-food supply chain.

This study conducted longitudinal qualitative research in a developing country with food loss challenges in the postharvest supply chain. This study collected data through multiple rounds of fieldwork, interviews and focus groups over four years. Thematic analysis and “sensemaking” were used for inductive data analysis to generate rich contextual knowledge by drawing upon the lived realities of the agri-food supply chain actors.

First, this study finds that the value losses are varied in the supply chain, encompassing production value, intrinsic value, extrinsic value, market value, institutional value and future food value. This happens through two cumulative effects including multiplier losses, where losses in one model cascade into others, amplifying their impact and stacking losses, where the absence of data stacks or infrastructure pools hampers the realisation of food value. Thereafter, this study proposes four strategies for moving from the loss-incurring current business model to a networked SBM for mitigating losses. This emphasises the need to redefine ownership as stewardship, enable formal and informal beneficiary identification, strengthen value addition and build capacities for empowering communities to benefit from networked SBM with AIS initiatives. Finally, this study puts forth ten propositions for future research in aligning AIS with networked SBM.

This study contributes to understanding the interplay between AIS and SBM; emphasising the integration of the two to effectively address food loss challenges in the early stages of agri-food supply chains. The identified strategies and research propositions provide implications for researchers and practitioners seeking to accelerate sustainable practices for reducing food loss and waste in agri-food supply chains.

This study aims to explore how a start-up entering maritime logistics networks (MLNs) in the container shipping industry integrates resources underlying value cocreation patterns in these networks.

The paper is based on a single case study of a technological start-up, providing tracking, tracing and other information services to MLN members using internet-based software. An interorganizational theory perspective informs the case study to unveil the resource integration for value cocreation in the network.

The start-up holds multiple resource interaction roles and the start-up’s involvement enables the creation of new knowledge resources, which facilitate new revenue streams and manage resource dependencies. Hence, the findings indicate that the start-up changes value cocreation patterns in the network by reconfiguring and integrating existing resources so that the service is customized for various customers, including shippers and freight forwarders.

The results provide insights about how technological start-ups can unlock resources within MLNs.

The study extends previous studies on resource roles in business networks and shows how start-ups can perform multiple roles simultaneously within these networks. In addition, the study contributes to the literature by studying information and knowledge as resources configured in different ways in a unique network setting.

The study aims to investigate the impact of technological innovation, such as blockchain, in the music field from a value co-creation perspective, highlighting how it is determining a radical change in the business model and value creation process.

To shed light on how blockchain adoption is reconfiguring the music industry, the authors adopted a qualitative-based approach based on a case study, allowing us to investigate value co-creation at three levels (macro, meso and micro) through exchange and integration of multi-actor resources.

The authors found that blockchain adoption in the music industry can singularly shape the business model, representing a powerful tool to enhance inter-organizational cooperation in value creation. It effectively deals with operational and business issues, besides financial transactions, profoundly impacting both the creation and distribution of value within the supply chain.

The research contributes to a better understanding of innovation adoption in a specific setting, the music industry, giving support and guidance for players working in this ecosystem. The blockchain-music link helps close the gap between music and society through technology, thus providing a foundation for future research.

The paper provides new insights into the antecedents and mechanisms of value co-creation, spanning macro-, meso-, and micro-levels of context. It also illustrates the factors underpinning Bitsong viability to embed the value co-creation perspective in designing the business model within a value network.

This paper explores international trade of the Chinese manufacturing industries through the lenses of network analysis (NA) to visualise the world trade network of the Chinese economy, describe its topology and better explain the international organisation of Chinese manufacturing industries.

The authors built a dataset of 40,550 Chinese companies and their 107,026 subsidiaries in 118 countries from Orbis-BVD and used a NA to investigate the connection between China and other countries. In particular, the authors studied the connections between Chinese companies and their subsidiaries in order to build a network of Chinese industries.

The authors found that the network of Chinese companies is ramified but not wide and it can be divided into two clusters. Moreover, the relations between China and other peripheral countries are strongly mediated by a few leading locations (e.g. Hong Kong and the USA).

This paper contributes to the literature in several ways. First, the authors provide empirical evidence on the magnitude and ramifications of Chinese enterprises in the world. The existing studies generally focus on applying NA to sectoral insights (Mao and Yang, 2012; Shaikh et al., 2016; Zheng et al., 2016; Wanzenbö ck, 2018; Krichene et al., 2019), whereas in this work the authors take a comprehensive view of the entire Chinese manufacturing system. Second, this paper complements the existing literature identifying the difference between cluster levels in Chinese manufacturing (Wu and Jiang, 2011) by proposing a cluster centralisation method to analyse the international network of Chinese firms rather than just the national network. Finally, the results also shed light on the international trade relationship between China, Hong Kong and the USA.

This study aims to explore the ways that social enterprises (SE) create value by embedding themselves in networks through the process of social innovation (SI). The processes of achieving common social missions were studied through selected organizations using an open approach to SI. Novel operational structures as well as unique forms of created value were explored.

Two organizations embedded in local and international networks were studied and were chosen due to their SI profiles. The study was based on qualitative exploratory research. In-depth analysis was conducted through interviews, open discussions, document analysis as well as personal observation to understand the dynamic interrelatedness of the main factors influencing success of SI ventures.

This paper identified the role of SI in SEs embedded in networks. Furthermore, the social value creation processes of these organizations as well as the value they create were explored. Based on the findings, SI is rooted in the personality of the included members of the network. The tools of collaboration are platforms that connect the network members to each other. The embedded organizations apply the concept of community sharing with the aim of social value creation.

By focusing mainly on system design principles, the sample consists of mainly those at the core of organizations in facilitator roles, leaving peripheral actor perceptions to be determined by secondhand observations.

While providing a general summary of factors influencing SI activities from extent literature, the paper mainly contributes by providing deeper insight into complex models of SI practices used by SEs. The paper further contributes to popularizing the growing role of SI activities in SEs.

The research question is how can a company implement a circular innovation in a supply network context? Leveraging the main conceptual and interpretative models of the industrial marketing and purchasing thinking, this study aims to investigate the interplay between the process of circular innovation development and the changes in the structure and dynamics of the supply network in which innovation takes place.

This research applies a case study design focusing on participant interaction dynamics. The case relates to an industrial company producing an innovative coating solution for compostable packaging. The data used to develop the case study came from multiple sources but primarily from semistructured interviews that cover the implementation of the circular innovation and the configuration of the circular network.

The dynamics of interconnected relationships can configure a circular network that interconnects business and non business actors through vertical, horizontal and heterogeneous relationships. The network configuration is supported by the new mobilizer actor that facilitates the sharing of circular knowledge within the circular network, together with the sharing of a market orientation and entrepreneurial orientation within the supply network, through the educational learning path.

This paper aims to contribute to a new understanding of how circular innovation can be developed, adopted and diffused. In a network, when circular innovation takes place, the focal issue is not the new product or technology in itself but how such innovation is developed and implemented by and through the reconfiguration of the business and non-business relationships into circular network.

Artificial intelligence (AI) models are demonstrating day by day that they can find long-term solutions to improve wastewater treatment efficiency. Artificial neural networks (ANNs) are one of the most important of these models, and they are increasingly being used to forecast water resource variables. The goal of this study was to create an ANN model to estimate the removal efficiency of biological oxygen demand (BOD), total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) at the effluent of various primary and secondary treatment methods in a wastewater treatment plant (WWTP).

The MATLAB App Designer model was used to generate the data set. Various combinations of wastewater quality data, such as temperature(T), TN, TP and hydraulic retention time (HRT) are used as inputs into the ANN to assess the degree of effect of each of these variables on BOD, TN, TP and TSS removal efficiency. Two of the models reflect two different types of primary treatment, while the other nine models represent different types of subsequent treatment. The ANN model’s findings are compared to the MATLAB App Designer model. For evaluating model performance, mean square error (MSE) and coefficient of determination statistics (R2) are utilized as comparative metrics.

For both training and testing, the R values for the ANN models were greater than 0.99. Based on the comparisons, it was discovered that the ANN model can be used to estimate the removal efficiency of BOD, TN, TP and TSS in WWTP and that the ANN model produces very similar and satisfying results to the APPDESIGNER model. The R-value (Correlation coefficient) of 0.9909 and the MSE of 5.962 indicate that the model is accurate. Because of the many benefits of the ANN models used in this study, it has a lot of potential as a general modeling tool for a range of other complicated process systems that are difficult to solve using conventional modeling techniques.

The objective of this study was to develop an ANN model that could be used to estimate the removal efficiency of pollutants such as BOD, TN, TP and TSS at the effluent of various primary and secondary treatment methods in a WWTP. In the future, the ANN could be used to design a new WWTP and forecast the removal efficiency of pollutants.

Disruptive shocks significantly compromise service contexts, challenging multidimensional value (co)creation. Recent focus has been on consumers experiencing vulnerability in service contexts. However, the susceptibility of service firms, employees and other actors to the impacts of disruptive shocks has received little attention. Since resource scarcity from disruptive shocks heightens tensions around balancing different needs in the service system, this paper aims to propose a framework of balanced centricity and service system resilience for service sustainability.

Adopting a conceptual model process, the paper integrates resilience and balanced centricity (method theories) with customer/consumer vulnerability (domain theory) resulting in a definition of multiactor vulnerability and related theoretical propositions.

Depleted, unavailable, or competed over resources among multiple actors constrain resource integration. Disruptive shocks nevertheless have upside potential. The interdependencies of actors in the service system call for deeper examination of multiple parties’ susceptibility to disruptive resource scarcity. The conceptual framework integrates multiactor vulnerability (when multiactor susceptibility to resource scarcity challenges value exchange) with processes of service system resilience, developing three research propositions. Emerging research questions and strategies for balanced centricity provide a research agenda.

A multiactor, balanced centricity perspective extends understanding of value cocreation, service resilience and service sustainability. Strategies for anticipating, coping with and adapting to disruptions in service systems are suggested by using the balanced centricity perspective, offering the potential to maintain (or enhance) the six types of value.

This research defines multiactor vulnerability, extending work on experienced vulnerabilities; describes the multilevel and multiactor perspective on experienced vulnerability in service relationships; and conceptualizes how balanced centricity can decrease multiactor vulnerability and increase service system resilience when mega disruptions occur.

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.

Understanding the outcomes of co-creation (CC) in healthcare is increasingly gaining multidisciplinary scientific interest. Although more and more service management scholars have pointed out the benefits of cross-fertilization between the various research fields, the literature on this topic is still scattered and poorly integrated. This study aims to summarize and integrate multiple strands of extant knowledge CC by identifying the outcomes of health CC and the determinants of these outcomes and their relationships.

A structured literature review was conducted per PRISMA guidelines. A total of 4,189 records were retrieved from the six databases; 1,983 articles were screened, with 161 included in the qualitative thematic analysis.

This study advances a comprehensive framework for healthcare CC based on a thorough analysis of the outcomes and their determinants, that is, antecedents, management activities and institutional context. Extant research rarely evaluates outcomes from a multidimensional and systemic perspective. Less attention has been paid to the relationship among the CC process elements.

This study offers an agenda to guide future studies on healthcare CC. Highlighting some areas of integration among different disciplines further advances service literature.

The framework offers an operational guide to better shape managerial endeavors to facilitate CC, provide direction and assess multiple outcomes.

This is the first extensive attempt to synthesize and integrate multidisciplinary knowledge on CC outcomes in healthcare settings by adopting a systematic perspective on the overall process.