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News media companies and human rights organizations have been increasingly warning about the rise of the surveillance state that builds on distrust and mass surveillance of its citizens. The COVID-19 pandemic is fostering digitalization and state-corporate collaboration, leading to the introduction of contact tracing apps and other digital surveillance technologies that bring about societal benefits, but also increase privacy invasion. This study examines citizens' concerns about their digital identity, the nation-state's intelligence activities, and the security of biodata, addressing their impacts on the trust in and acceptance of governmental use of personal data. Our analysis of survey data from 1,486 Canadians suggest that those concerns have negative impacts on citizens' acceptance of governmental use of personal data, but not necessarily on their trust in the nation-state being respectful of privacy. Government and corporations, it is concluded, should be more transparent about the collection and uses of data, and citizens should be more active in "watching the watchers" in the age of Big Data. ; Peer reviewed

PurposePurchasing has emerged as a key source of competitive advantage. This paper aims to explore how different purchasing strategies are connected to complex supply relationships and to the goal of purchasing.Design/methodology/approachThe study draws on the literature on industrial network theory and industrial buying behaviour.FindingsThe contribution describes six types of purchasing strategies that firms exert. These strategies depend on the complexity of supply relationships and the buyer's purchasing goal. Conventional products and services are bought through transactional exchange relationships, whereas strategically important items are purchased through intentional supply networks.Practical implicationsPurchasing strategies of a firm emphasise either efficiency or effectiveness of operation. The type of exchange varies according to the nature of supply relationships: it is either transactional or relational. A key implication for managers is that they should recognise the goal of buying, the strategic importance of the object of purchasing, and choose accordingly between the different types of supplier structures.Originality/valueThe paper shows that firms' purchasing strategies depend on the nature of their supply relationships and the motive for purchasing. Different strategies emphasise different aspects and events that ultimately manifest themselves in the firms' business models.

This study applies a machine-learning technique to a dataset of 38,000 textual comments from Canadian small business owners on the impacts of coronavirus disease 2019 (COVID-19). Topic modelling revealed seven topics covering the short- and longer-term impacts of the pandemic, government relief programs and loan eligibility issues, mental health, and other impacts on business owners. The results emphasize the importance of policy response in aiding small business crisis management and offer implications for theory and policy. Moreover, the study provides an example of using a machine-learning–based automated content analysis in the fields of crisis management, small business, and public policy.

PurposeThis study sets out to examine the relationship between firms' learning orientation and network collaboration. The aim is to investigate how learning orientation enhances network collaboration and to discuss the role of the co‐innovation focus in the learning orientation‐network collaboration relationship.Design/methodology/approachBased on a partial least squares (PLS) structural equation modeling analysis of 90 small and medium‐sized industrial firms (SMEs), the study tests hypotheses regarding how two diverse learning orientations – i.e. exploration and exploitation – precede firms' network collaboration.FindingsThe analysis shows that learning drives firms' co‐innovation focus in terms of product and process co‐innovation. In particular, the explorative learning orientation is found to foster firms' network collaboration through product co‐innovation. Exploitative learning orientation promotes process innovations but discourages networking.Practical implicationsA key implication for business practitioners is the understanding that SMEs' explorative learning approaches drive their network collaboration. The development of novel product innovation calls for learning with partners in inter‐organizational networks, whereas process improvements rely on the firm's intra‐organizational learning.Originality/valueThe paper provides evidence of the connection between firms' learning orientation, co‐innovation focus, and networking. Thus, it contributes to the literature on organizational learning, innovation management, and business networks by explicating how learning drives a firm's networking through its co‐innovation focus.

There are growing internal and external pressures for traceability in food supply chains due to food scandals. Traceability refers to tracking food from the consumer back to the farm and vice versa for quality control and management. However, many traceability solutions have failed to meet the needs of supply chain stakeholders. Blockchain is a novel distributed database technology that could solve some issues of traditional traceability systems, such as cost of adoption and vulnerabilities to hacking and data tampering. This study aims to gain insights on the benefits of applying blockchain technology for traceability in food supply chains through literature review and an investigation of five companies that are experimenting with blockchain-based food traceability. Our findings suggest that, upon implementation and contribution by all supply chain participants, blockchain-based traceability can provide cost-savings, reduced response time to food scandals and food-borne illness outbreaks, improved security and accuracy, better compliance with government regulations, and thus increase consumer trust. ; Peer reviewed

Purpose
This study aims to understand their emergence and types of business models in the Internet of Things (IoT) ecosystems.


Design/methodology/approach
The paper builds upon a systematic literature review of IoT ecosystems and business models to construct a conceptual framework on IoT business models, and uses qualitative research methods to analyze seven industry cases.


Findings
The study identifies four types of IoT business models: value chain efficiency, industry collaboration, horizontal market and platform. Moreover, it discusses three evolutionary paths of new business model emergence: opening up the ecosystem for industry collaboration, replicating the solution in multiple services and return to closed ecosystem as technology matures.


Research limitations/implications
Identifying business models in rapidly evolving fields such as the IoT based on a small number of case studies may result in biased findings compared to large-scale surveys and globally distributed samples. However, it provides more thorough interpretations.


Practical implications
The study provides a framework for analyzing the types and emergence of IoT business models, and forwards the concept of "value design" as an ecosystem business model.


Originality/value
This paper identifies four archetypical IoT business models based on a novel framework that is independent of any specific industry, and argues that IoT business models follow an evolutionary path from closed to open, and reversely to closed ecosystems, and the value created in the networks of organizations and things will be shareable value rather than exchange value.

PurposeThis paper seeks to explore how market orientation facilitates the strategic flexibility of business models grounded in open innovation. The authors suggest that the new paradigm of open innovation may impact a firm's adaptability and responsiveness under conditions of environmental flux. However, extending innovation capacity by opening the innovation process poses major challenges for firms. The aims of this study are to explore the characteristics of open innovation activity and to contemplate the role of strategic flexibility in the design of business models based upon open innovation.Design/methodology/approachThe study draws upon a qualitative research approach through a longitudinal case study in the field of open source software (OSS). The empirical case illustrates how an OSS firm utilizes signals in its environment to flexibly alter its business model.FindingsA business model that embodies open innovation raises dilemmas between open and closed innovation paradigms. However, the authors' case highlights that an ambidextrous approach that combines market orientation with the principles of open innovation increases profitability, shortens time to market through effective market access, and enhances innovation capability.Research limitations/implicationsThe results have profound implications for industrial marketers, managers, management consultants and business educators. They can use the insights gleaned from this research to guide the development of business models that involve open innovation. The results indicate that firms involved in open innovation need reactive strategic flexibility to cope with the environmental diversity and variability. However, this study analyzes a single case in the field of OSS and one should be cautious when generalizing the findings.Originality/valueThis paper improves the understanding of the relationship between flexibility and market orientation. It combines two areas that have previously been discussed separately, i.e. market orientation and open innovation.

Living labs (LLs) are becoming an increasingly popular approach to engage in open innovation. Although applications and influence of LLs have grown rapidly over the last decade, the landscape of LL research remains largely unclear and underexplored. Hence, there is an urgent need to develop a consolidated understanding of this research field and to detect the potential areas of fragmentation and isolation. Through a systematic review of the scholarly literature on LLs, this study applies bibliometric methods on a dataset of 411 journal articles. The results of this study reveal the diverse and fragmented nature of the LL field, with contributions spanning across different disciplines and application domains. Despite such fragmentation, some clusters of scholars and publications are identified as well as influential contributions. Given the nascent state of the literature, the role of special issues in shaping the evolution of the LL debate is prominent. This study provides a map to practitioners to investigate and learn from the application of LLs in diverse fields. This aspect is particularly important in light of the current COVID-19 pandemic, which stresses the key role of open and collaborative approaches to innovation, making the use of LLs increasingly relevant for governments, companies, public organisations and individuals.

PurposeThis study aims to focus on living labs as a means of achieving radical innovation by discussing the differences in their network structure and its effect on the type of innovation outcome.Design/methodology/approachThis research analyses 24 living labs in four countries using qualitative methods.FindingsA specific network structure referred to as a distributed multiplex supports radical innovation in living labs, while distributed and centralized network structures support incremental innovations. Also, the results suggest that radical innovation depends on the driving actor and objectives in a living lab.Research limitations/implicationsA bias on the perceived novelty of innovation may exist when analyzing data collected through interviews with a limited number of living lab participants compared to a large number of informants. This study proposes a two-dimensional framework based on the network structure to investigate innovation in living labs.Practical implicationsThis paper offers a classification tool to identify, categorize and make sense of organizations' participation in open innovation networks and in living labs.Originality/valueThe study provides evidence that, although the distributed multiplex network structure supports the emergence of radical innovations, the distributed and centralized network structures support incremental innovation. A combination of a provider- or utilizer-driven living lab and a distributed multiplex network structure, with a clearly defined and future-oriented strategic objective, offers good potential for radical innovation to occur.