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This study examines the collaborative value practices of cause-based social entrepreneurship alliances. We investigate key drivers of value creation in such alliances.

The study utilizes a longitudinal case study design approach involving four northern Italian businesses for investigating the cause-based social alliances.

The study findings suggest that cause-based alliance differ from other business relationships due to social mission of the alliance and orientation of partners to a specific social cause. However, over time involved firm may pursue commercial interests.

The study utilizes a qualitative case study approach to examine the issues. This may have implications on generalizability of study findings. Further, the sample is limited to small firms, which limit its relevance for large firms.

Managers can utilize the study findings to guide the organizing process of a successful cause-based alliance and can implement it with positive outcomes for their firm.

This is one of the first study on the emerging phenomenon of cause-based social alliance. It contributes to the literature on social entrepreneurship. It informs and guides practitioners about motivations and drivers of such alliances.

This study aims to present an overview of leading research trends in the lean six sigma domain published in the International Journal of Lean Six Sigma (IJLSS) since its inception.

The study analyses articles published between 2010 and 2019 in IJLSS using the bibliometric technique. The results of data analysis identify the most prolific authors, their affiliation, citation trends and highly cited articles from the journal. Further, a graphical analysis involving bibliographic coupling and co-citation analysis of the corpus enriches the investigation.

The results of the bibliometric analysis suggest that the number of IJLSS’s publications and citations grew markedly over time (from 4 citations in 2010 to nearly 1,324 in 2019). The organizational diversity and collaboration among authors publishing in IJLSS are trending upwards. Case study and focus group are the two most common research designs in publications. In the study, three major themes emerged: implementation of lean on business, integration of lean and six sigma and the effects of lean six sigma on businesses.

The study finding informs and educates practitioners and scholars about various qualitative research tools, applications and methods of implementing lean six sigma tools in different industry sectors.

The study uses bibliometric analysis to propose a novel categorization of research published in IJLSS and to report on the utilization of various lean tools in the journal. The study provides guidance for new future research besides offering a thorough introspection of the lean and six sigma domains.

The booming of the Internet of things (IoT) and artificial intelligence (AI) techniques contributes to knowledge adoption and management innovation for the healthcare industry. It is of great significance to transport the medical resources to required places in an efficient way. However, it is difficult to exactly discover matched transportation resources and deliver to its destination due to the heterogeneity. This paper studies the medical transportation resource discovery mechanism, leading to efficiency improvement and operational innovation.

To solve the transportation resource semantic discovery problem under the novel cloud environment, the ontology modelling approach is used for both transportation resources and tasks information modes. Besides, medical transportation resource discovery mechanism is proposed, and resource matching rules are designed including three stages: filtering reasoning, QoS-based matching and user preferences-based rank to satisfy personalized demands of users. Furthermore, description logic rules are built to express the developed matching rules.

An organizational transportation case is taken as an example to describe the medical transportation logistics resource semantic discovery process under cloud medical service scenario. Results derived from the proposed semantic discovery mechanism could assist operators to find the most suitable resources.

The case study validates the effectiveness of the developed transportation resource semantic discovery mechanism, contributing to knowledge management innovation for the medical logistics industry.

To improve task-resource matching accuracy under cloud scenario, this study develops a transportation resource semantic discovery procedure from the viewpoint of knowledge management. The novel knowledge management practice contributes to operational management of the cloud medical logistics service by introducing ontology modelling and creative management.

Companies vary in their attitudes toward regulatory (ethics) risk. The purpose of this study is to assess how regulatory risk‐averse, risk neutral and risk seeking companies employ distinct managerial risk and slack accumulation strategies and differ in their auditor scores and bankruptcy risk.

The authors test their hypotheses using the GAO‐assembled database of financial restatements that allows contrasting voluntary restaters (firms that restated without being prompted either by external auditors or the SEC) and forced restaters (firms requested to restate by the SEC or external auditors). The paper uses logistic regression for comparing different groups of firms to test the hypotheses.

The results of the data analysis mostly supported the hypotheses. The findings suggest that a firm's attitude towards regulatory risk is associated with organizational slack (available and potential), risk (managerial and organizational), and auditor's rating.

Some limitations of the study are: use of cross sectional data does not allow testing causal effects, relying on GAO office for categorizing firms in different regulatory category introduces the possibility of bias in analysis, and use of only North American firms in the sample limits the generalizability of the findings.

Firms' attitudes toward regulatory risk and their respective risk and slack management strategies could be used to detect fraud early on before such firms transgress from the realm of legality to borderline legality and illegality.

Some contributions of the study are: it shows that a firm's fraud tendency or regulatory risk behavior is associated with the type of slack accumulated and available in the firm, regulatory risk‐averse companies take less managerial and bankruptcy risks, and earn higher evaluations from auditors, it demonstrates that regulatory risk‐averse companies differ from regulatory risk neutral companies.

This study aims to investigate the complex relationship between green intellectual capital (GIC), green human resource management (GHRM) and green innovation (GI) for improvement in the environmental performance (EP) of an organization.

The data collected from 456 food manufacturing firms in Pakistan was used for structural equation modeling through SmartPLS. Hypotheses were tested through path analysis, predictive relevance and effect size of variables.

The findings show that GIC and GHRM have no direct impact on EP; instead, GI plays a mediating role to make GIC and GHRM helpful in improving an organization’s EP. Also, the environmental strategies play a significant role in the EP and act as a moderator in the relationship between GI and EP.

The Global Climate Risk Index has ranked Pakistan as the fifth most vulnerable to climate change. Industrial activities are contributing significantly to carbon emissions, and therefore, it is vital to mitigate and adapt to climate change to improve the organization’s EP. The findings of this study show that GIC, GHRM and GI can significantly enhance the EP of food manufacturing firms in Pakistan.

The authors propose a theoretical basis for understanding the role of ecosystem intermediaries in the configuration of social entrepreneurship identities in social purpose organisations (SPOs) and their business model innovations (BMIs).

Adopting a retrospective multiple-case study, the authors offer insights into the paths/elements that determine the building of 44 social entrepreneurship identities in the context of an emerging economy (Mexico).

The study sheds light on the role of intermediaries in the configuration of the entrepreneurial identities of Mexican SPOs and BMIs, as well as several externalities generated during the process of capturing the social and economic value, especially when social innovations are focussed on solving societal, economic and ecological social problems.

The first limitation is related to the analysis of intermediaries within the social entrepreneurship ecosystem, which needs more conceptual and empirical evidence. The second limitation is that the analysis focussed only on intervened SPOs, as the authors did not control for non-intervened SPOs. Thus, this allows for future in-depth analysis of intermediary efficiency in a focus group (intervened SPOs) and a control group (non-intervened SPOs).

The study also provides insights for Mexican SPOs on how a social entrepreneurship identity helps to capture the value creation of social innovations within an innovation ecosystem. Indeed, it is strongly aligned with the United Nations' Social Development Goals.

The study enhances the discussion about how intermediaries could encourage social entrepreneurial identity, as well as how intermediary intervention could facilitate the design and implementation of BMIs in the innovation ecosystem.

To further extend the understanding of the aggregating functions of an entrepreneurial business network, this paper attempts to explore the antecedents enabling the organisation of diverse entrepreneurs to engage in a collaborative inter-firm business network project. This paper also elucidates the development of the relational capabilities and performance of entrepreneurial business networks.

An explorative, longitudinal case study design is employed to analyse an Italian agricultural business network, which comprised a group of local small- and medium-sized enterprises (SMEs). Using the network as the focus of analysis, the case study draws insights from key informants comprising the network management team and the entrepreneurs who make up the membership of the business network.

The results of the study provide critical factors for successful organisation of inter-firm engagement. Although these factors are not mutually exclusive, the results show that organising for inter-firm engagement in an entrepreneurial business network context positively influenced the network relational performance and entrepreneurs' innovation capabilities.

The paper extends current understanding of inter-organisational engagement and illuminates the antecedents enabling the development of network relational dynamics capabilities. The empirical results provide unusual insights into the aggregating roles of an entrepreneurial business network, giving practitioners practical insights into managing a successful inter-organisational collaborative project. Using the relevant theoretical frameworks, the study empirically tests the organisation solutions relevant to literature on inter-firm engagement in a business network context and addresses the organisation solutions' interrelationship and linkages to entrepreneurial network relational performance in terms of knowledge practice, information and resources sharing and innovation.

This chapter explores the significance of blockchain technology in protecting data for intelligent applications across various industries. Blockchain is a distributed ledger that ensures the immutability and security of transactions. Given the increasing need for security measures in industries, understanding blockchain technology is crucial for preparing for its future applications.

This chapter aims to examine the use of blockchain technology across industries and presents a compilation of existing and upcoming blockchain technologies for intelligent applications. The methodology involves reviewing research to understand the security needs of different industries and providing an overview of methods used to enhance multi-institutional and multidisciplinary research in areas like the financial system, smart grid, and transportation system.

The findings highlight the benefits of blockchain networks in providing transparency, trust, and security for industries. The Responsible Sourcing Blockchain Network (RSBN) is an example that utilizes blockchain's decentralized ledger to track sustainable sourcing from mine to final product. This information can be shared with auditors, corporate governance organizations, and customers.

The practical implications of this chapter are significant, serving as a valuable resource for industries concerned with identity privacy, traceability, immutability, transparency, auditability, and security. Understanding and implementing blockchain technology can address the growing need for secure and intelligent applications, ensuring data protection and enhancing trust in various sectors.

The main goal of this paper is to study the cloud service discovery mechanisms. In this paper, the discovery mechanisms are ranked in three major classes: centralized, decentralized, and hybrid. Moreover, in this classification, the peer-to-peer (P2P) and agent-based mechanisms are considered the parts of the decentralized mechanism. This paper investigates the main improvements in these three main categories and outlines new challenges. Moreover, the other goals are analyzing the current challenges in a range of problem areas related to cloud discovery mechanisms and summarizing the discussed service discovery techniques.

Systematic literature review (SLR) is utilized to detect, evaluate and combine findings from related investigations. The SLR consists of two key stages in this paper: question formalization and article selection processes. The latter includes three steps: automated search, article selection and analysis of publication. These investigations solved one or more service discovery research issues and performed a general study of an experimental examination on cloud service discovery challenges.

In this paper, a parametric comparison of the discovery methods is suggested. It also demonstrates future directions and research opportunities for cloud service discovery. This survey will help researchers understand the advances made in cloud service discovery directly. Furthermore, the performed evaluations have shown that some criteria such as security, robustness and reliability attained low attention in the previous studies. The results also showed that the number of cloud service discovery–related articles rose significantly in 2020.

This research aimed to be comprehensive, but there were some constraints. The limitations that the authors have faced in this article are divided into three parts. Articles in which service discovery was not the primary purpose and their title did not include the related terms to cloud service discovery were also removed. Also, non-English articles and conference papers have not been reviewed. Besides, the local articles have not been considered.

One of the most critical cloud computing topics is finding appropriate services depending on consumer demand in real-world scenarios. Effective discovery, finding and selection of relevant services are necessary to gain the best efficiency. Practitioners can thus readily understand various perspectives relevant to cloud service discovery mechanisms. This paper's findings will also benefit academicians and provide insights into future study areas in this field. Besides, the drawbacks and benefits of the analyzed mechanisms have been analyzed, which causes the development of more efficient and practical mechanisms for service discovery in cloud environments in the future.

This survey will assist academics and practical professionals directly in their understanding of developments in service discovery mechanisms. It is a unique paper investigating the current and important cloud discovery methods based on a logical categorization to the best of the authors’ knowledge.