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The purpose of this paper is to support effective business services provision along the life cycle of complex service-enhanced products, such as the case of solar power plants, and to explore collaborative approaches for multi-stakeholder business services.

Design and implementation of adequate collaboration strategies and cloud-based support mechanisms to facilitate creation and management of collaborative networks in this sector. For this purpose, a conceptual framework, a cloud-based platform and a set of collaboration support tools are proposed. Validation is based on a pilot implementation and interactions with a large group of end users.

Validation results confirmed the suitability of the collaborative networks approach in this sector, which often involves multiple small and medium size enterprises.

The interplay between long-term strategic networks and goal-oriented collaborative networks and their interaction with the various phases of the product-services life cycle correspond to a novel approach in this sector, traditionally focused on a sub-contracting model. This opens new opportunities for enhancing the value of complex products through collaborative value-added services. Of particular relevance is also the adoption of collaborative approaches for service co-creation.

Various networked organizational forms already exist in the market today, however, all of them share the same problem – lack of fast and objective procedures for partners’ selection when addressing a particular project. The purpose of this paper is to solve such problems by offering an alternative to the existing global market layout, dominated by large corporations.

This research belongs to the category “fuzzy decision making and multi-attributive decision making,” since it is using methodologies such as the analytical hierarchy process (AHP), the fuzzy-AHP approach, and the Technique for Order of Preference by Similarity to Ideal Solution.

The authors defend that appropriate partner selection is a vital success factor in any collaboration.

The authors have designed a sustainable partner network solution for the field of machinery. Nevertheless, the proposed approach is adaptable to other fields also, whereas the focal player or project owner selects the best partner based on a set of criteria.

The paper includes a feasibility case study for the approval of findings, where several small and medium enterprises (SMEs) from the field of machining collaborate to achieve a common goal.

The research focuses on production enterprises (especially for SMEs) and is intended to improve their competitiveness. Small enterprises combining into a network makes it possible to compete with large corporations and helps to decrease project initiation time and project realization risks.

The main idea is to collect information about the available resources of SMEs into a new temporary entity and to utilize those resources for the realization of the tasks of a particularly large project, while meeting customer expectations. In addition, this work also suggests a calculation tool for faster partner evaluation (assessment) based on various criteria for each particular project.

Normalization is a crucial step in all decision models, to produce comparable and dimensionless data from heterogeneous data. As such, various normalization techniques are available but their performance depends on a number of characteristics of the problem at hand. Thus, this study aims to introduce a recommendation framework for supporting users to select data normalization techniques that better fit the requirements in different application scenarios, based on multi-criteria decision methods.

Following the proposed approach, the authors compare six well-known normalization techniques applied to a case study of selecting suppliers in collaborative networks.

With this recommendation framework, the authors expect to contribute to improving the normalization of criteria in the evaluation and selection of suppliers and business partners in dynamic networked collaborative systems.

This is the first study about comparing normalization techniques for selecting the best normalization in dynamic multiple-criteria decision-making models in collaborative networks.

This study aims to carry out the critical assessment of success factors of mass collaboration in the context of retail companies operating in Jordan.

This study is quantitative in nature in which data has been gathered from the primary sources of information through a survey questionnaire. The employees and managers from the retail sector of Jordan have been considered. Confirmatory factor analysis has been carried out to determine the reliability and validity of the factors that are included in the research model. Quality of model and predictive prevalence has been tested with the help of determining the R-square of the model. Path assessment has also been done as a part of data analysis to assess the statistical significance of the association between different factors and the success of a mass collaboration.

The analysis determined that organizational structure, the mechanism in collaborative learning along with technologies adopted in collaborative learning, evaluation of learner’s performance and quality of knowledge has a significant effect on mass collaboration within the context of the retail sector in Jordan.

The context of this research is the Jordanian retail sector; hence, it is very concise and cannot be necessarily applied within the context of other industries. This research has adopted a quantitative design where the data was collected with the help of a survey questionnaire based on the close-ended questionnaire. This has limited the answers to the available options given.

The originality of this study has been ensured by carrying out a primary survey with the employees and managers belonging to the Jordanian retail sector to the promising approach to create agile knowledge and share to enhance the organizational context.

Digitalization had a relevant impact on the cultural tourism sector, both demand and supply. If, on the one hand, advances in digital technologies provided tourists with new mobile services able to amplify the cultural experience, on the other hand, they catalyzed the development of new business models by digital enterprises. This paper has a twofold purpose: to detect business models and key characteristics of mobile apps for cultural tourism and to analyze the offering of app-based services in this sector.

The authors defined a methodology to identify, characterize and analyze a particular category of digital products for cultural tourism: app-based services. They are studied in terms of value creation, proposition and capture with the aim to identify the distinctive features of business models. As a result, the authors identified a classification framework on three main dimensions, namely “how to exploit mobile app features to create value for cultural tourists” (value creation), “which valuable services are delivered to cultural tourists” (value proposition) and “how companies are rewarded for the value they offered” (value capture). The authors apply the framework to perform a situation analysis of app-based services in the cultural tourism market.

The analysis highlights that digital enterprises offering app-based services do not fully exploit advances in technologies about users' value requirements. Hence, the results of our work suggest some directions that digital enterprises may follow to better exploit mobile app technology.

To date, little research has been devoted to investigating cultural tourism business models involving the exploitation of mobile app-based services. This research provides a useful framework to analyze fundamental aspects of business models in this sector. Such a framework represents a practical tool that provides fruitful insights for the design of a new generation of app-based services within the so-called “Internet of things” domain.

Although prior studies have identified several technologies related to Industry 4.0 and their individual potential, it is still unclear how these technologies could be integrated to achieve better results. Based on this, we propose several collaborative networks combining technologies associated with Industry 4.0.

A literature review was performed using a research model to support the evaluation and identification of key and collaborative technologies related to Industry 4.0. We examined these technologies using hierarchical cluster analysis and principal components analysis, based on their characteristics.

The study identified big data, cloud computing, the internet of Things and cyber-physical systems as key technologies for Industry 4.0, and a further eight collaborative technologies that are strongly related to industrial performance. We found five collaborative networks with distinct goals in the context of Industry 4.0: (1) smart manufacturing; (2) technological platforms; (3) market reactiveness; (4) smart products and (5) flexibility.

The findings allowed us to create five pathways for future work on Industry 4.0 technologies via collaborative networks. In practice, this will help managers to improve their focus on priorities regarding the implementation of Industry 4.0 technologies.

This study provides insights into how to establish links between technologies through collaborative networks for certain purposes. In addition, we propose five future directions for these collaborative networks that require further investigation by researchers.

This paper aims to present Accomm a software implementation of Ágora-SN, a supply network (SN) customer-oriented model integrated with an Adaptation Model. Accomm serves two purposes: as an experimental validation tool to measure the impact of Adaptation on an agribusiness SN model and as a logistic and marketing operations planning assistant.

The design of Accomm is based on the results of the Ágora-SN model that comprises the following tasks: to characterize the SN actors’ processes ( composed of multiple first-tier suppliers, a focal company and multiple first-tier customers), identifying the ones oriented to the customer; to integrate these processes into a SN model which incorporates a supplier cooperation model; and to provide an adaptation model that implements a customer profile and a context profile to improve order fulfillment.

To validate the Ágora-SN model, a prototype Accomm was created referred to a real Colombian agribusiness sector company, specifically in the floriculture sector. This prototype was validated through two methods: a usability scale and a set of scenarios that compared the application’s behavior with and without adaptation and cooperation. The application provides a better response to demand when both adaptation and cooperation are enabled.

This work was tested in an academic environment and was validated by different experts. Further tests in operational real-life environments are required to fully validate the approach.

The main contribution of this work is the integration of Adaptation into a SN model as a way to center the SN toward the customer. As an additional contribution, the validation tool Accomm is conceived as an operational planning tool for agribusiness SN.

This study aims to explore the relationships among the five components of supply chain (SC) resilience (SCRES): visibility, velocity, flexibility, robustness and collaboration and their impacts on the SC performance under disruption (SCPUD).

Five SCRES components are identified from the literature review and data are collected using an web survey from 113 manufacturing companies in Taiwan. The data are analyzed by structured equation modeling with the partial least square solution. Two-stage least-squares (2SLS) regression was used to test the potential endogeneity of SC collaboration (SCC).

The results reveal that SCC is an exogenous driver of SCRES; it directly affects visibility, velocity, flexibility, robustness and SCPUD. Furthermore, SC flexibility is the only component of SC agility that directly affects SCPUD; it is influenced directly by SC velocity and indirectly by SC visibility through SC velocity. SC visibility is a vital agility component that positively influences SC velocity and SC robustness.

The data in this study are cross-sectional and the sample size of 113 is relatively small. The relationship between SC robustness and SCPUD needs a longer observation period to reveal. The logistic issue in the shortage of carriers caused by the pandemic has been overlooked.

A firm should enhance its collaboration and flexibility in the SC as they both are the critical antecedents of SC performance (SCP) during the disruption period.

This study integrates visibility, velocity, flexibility, robustness and collaboration into a complete framework of SCRES. The dependent variable, SCPUD, measures SC performance (SCP) under the disruption caused by the COVID-19 pandemic. It is the first study to investigate the associations of the six constructs in a research model.

To share the authors' view for an enterprise formation, and a product assembly using communication and information technology in economic manner.

Comparison of the proposed system with a conventional systems. The study explains the approach with a case study.

Shows the approach abilities and the minimization cost of the product.

This approach shows communication and information technology effects on the manufacturing and assembly.

The paper has a new look on the enterprise formation, assembly, and manufacturing.