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Due to the constantly increasing competitiveness along with the complexity of knowledge, firms perceive collaboration as a key strategy that preserves firms' radical innovation performance. In this context, this paper aims to examine how firms’ partners’ diversity in open innovation activities influences the development of radical innovations, critical for social development. In particular, this study analyzes how the functional and geographical breadth of the firm’s collaboration portfolio affects its radical innovation performance. Furthermore, it also explores the role of firm size as a moderator in the relationships proposed.

This research employs panel data analysis, using a sample of 4,677 Spanish firms, with data sourced from the PITEC database.

The results of this study show that there is an inverted U-shaped relationship between the functional and the geographical breadth of collaborations and the firms’ radical innovation performance. Moreover, this study finds partial support for the moderating role of firm size, in the sense that small and medium-sized enterprises (SMEs) and large firms vary in their optimal number of diversity of partners.

This research provides a better understanding on how partners’ functional and geographical diversity, along with organizational characteristics such as firm size, affect how firms benefit from collaboration for innovation. This study shows that both SMEs and large firms experience diminishing returns when their collaboration networks become overly diverse in pursuit of radical innovation, due to increased costs. However, in SMEs, the turning point occurs at a later stage, consistent with the idea that small firms need broader functional networks to access complementary and novel resources they usually lack.

This chapter discusses how the real options theory can be useful for understanding the adoption of human resources management (HRM) practices. The authors review how the real options theory has provided insights into the processes through which firms manage uncertainties involved in the adoption of HRM practices. The authors offer propositions for future HRM research from the real options perspective. The authors contend that analyzing HRM practice adoptions through the lens of real options theory can enhance our understanding of the mechanisms through which firms choose which HRM practices to adopt and how they adjust the timing, scale, and methods of investment in these practices. Specifically, the authors suggest that differences in information relevant to valuation of HRM options are the source of distinct choices of HRM options across firms. Finally, the authors propose advancing knowledge on HRM practice adoptions by using a portfolio of options approach, as well as considering factors like competitors, path dependence, and switching options.

Since previous literature provides fragmented and conflicting results about the use of digital data for product innovation, the article aims to comprehensively explore and shed light on how agri-food firms utilise external and internal digital data sources when dealing with different product innovations, such as incremental, architecture and radical innovation.

This paper adopts an exploratory multiple-case study and a theory-building process, focussing on the agri-food industry. We collected primary and secondary data from eight manufacturing companies.

The findings of this research show an empirical framework of six agri-food firms’ digital data utilisation behaviours: the supervisor, the passive supervisor, the developer, the passive developer, the pathfinder and the conjunction behaviour. These digital data utilisation behaviours vary according to a combination of data sources, such as internal data related to inside phenomenon measures (e.g. data generated by sensors installed in the production plan) or external data (e.g., market trends, overall sector sales), and innovation purposes.

This article offers guiding principles that assist agri-food companies when utilising internal and external digital data sources for specific product innovation outcomes such as incremental, architectural and radical innovation.

The significance of external and internal data sources in stimulating product innovation has garnered substantial attention within academic discussions, highlighting the critical importance of analysing digital data for driving such innovation. Nonetheless, the predominant approach is to study a single innovation outcome through the lens of digital technology. In contrast, our study stands out by adopting a fundamental perspective on data sources, enabling a more nuanced explanation of the overall product innovation outcomes within the agri-food sector.

Members in the international joint ventures (IJVs) for high-speed rail (HSR) projects usually engage in coopetition interactions to create common benefits (CB) and simultaneously safeguard private benefits (PB). Previous studies of coopetition and performance using variance-based methods usually ignore the combinational influence of diverse coopetition constructs on performance, which can be effectively compensated by adopting a configuration perspective. Therefore, this research aims to ascertain various combinations of three coopetition constructs (coopetition relationship, coopetition capability and coopetition strategy) that lead to high IJVs’ performance through a configuration approach.

First, the research framework of coopetition configuration was established, and the key constructs were operationalized, which were validated by expert interviews. Then the information on 12 HSR IJVs was collected and quantified through nine rounds of interviews and a questionnaire survey. Later, the fuzzy-set qualitative comparative analysis (fsQCA) was applied to explore what coopetition configurations benefit the CB or PB achievement.

Configuration results indicate that six coopetition configurations lead to CB outcome and seven configurations lead to PB outcome. Based on the results, coopetition contexts are divided into four categories: firm-based coopetition, project-based coopetition, firm-project-based coopetition and none-based coopetition. Then, a selection scheme for coopetition strategies in various contexts has been developed. The results also show that the core conditions mostly appear in the coopetition relationships and coopetition strategies dimensions, and the optimal coopetition strategies vary in different contexts.

This study enhances the theoretical understanding of coopetition in HSR IJVs and assists relative HSR industrialists, as well as the mega infrastructure project managers, in IJVs’ implementation. The configuration perspective of this paper also contributes to a systemic and holistic view of coopetition in HSR IJVs.

The study aims to develop a hierarchical model for innovative work behaviour (IWB) that can capture the complex associations among the factors contributing to IWB within the information technology (IT) sector. To accomplish this, the authors rely on an abductive approach using a graph theoretic model, often called interpretive structural modelling (ISM).

After conducting an in-depth literature review and using the Delphi method, the authors identified 12 factors (11 enablers and IWB as an outcome). The authors collected data through the Delphi approach by sending the questionnaire to 11 experts from academia and the IT sector who have extensive experience and knowledge relevant to the study. The authors then used the ISM method to analyse the relationships among these factors and understand their driving forces.

Based on the ISM model and the Matrice d'Impacts Croisés Multiplication Appliquée à un Classement analysis, the authors have identified that inclusive leadership, proactive personality and knowledge creation ability are the variables with strong driving power but weak dependence. Conversely, IWB has strong dependence but weak driving power. These findings suggest that to foster IWB, the organisation should prioritise inclusive leadership, proactive personality and knowledge-creation ability to succeed in challenging times. The study’s findings contribute to the social exchange theory, which explains IWB in a dynamic setting. Additionally, the study helps address the significant concerns that most IT companies face during times of crisis.

The study provides valuable guidance for managers and policymakers who are grappling with the challenges of improving IWB in the IT sector. This study is particularly relevant as the industry is currently navigating an economic recession and facing intense competition from other tech companies launching new products and services.

This research holds great significance for top executives, line managers and policymakers in the IT industry. It sheds light on the relevance and importance of various factors facilitating millennials' IWB.

The purpose of this paper is to explore networked business models on a nascent market for a sustainable innovation.

The study takes a qualitative approach through a comparative case study of three solar photovoltaic (PV) parks in Sweden. Data was collected from 14 interviews with multiple supply chain and network actors as well as secondary data. Industrial marketing and purchasing is applied for theoretical framing.

The study demonstrates transactional, relational, environmental and social drivers for participating in the network. The study reveals the duplicity of the nascent market, which encourages supply chain actors to develop their individual business models to take a larger market share or become future competitors to current collaborators. On the nascent market with few developed regulations, the network enables actors to influence regulations on local and regional levels.

The study is limited to the nascent solar PV industry in Sweden, which is characterized by institutional turbulence, market uncertainties and few established supply networks.

Practitioners need to consider multifarious drivers for participating in networked business models, where the economic driver may be the least motivating.

This study provides several multiactor business models and classifies them into specific applications and general applications. The study provides unique insight into the complexity of interactions among supply chain actors in networked business models on a nascent market for sustainable innovation. Due to the scarcity of available partners on the nascent market, actors need to look beyond their on-going relationships and their network horizon, or actors’ roles evolve to include activities that was not part of their individual business models.

Heating, ventilating, air-conditioning and cooling (HVAC) systems are crucial in daily health-care facility services. Design-related defects can lead to maintenance issues, causing service disruptions and cost overruns. These defects can be avoided if a link between the early design stages and maintenance feedback is established. This study aims to use experts’ experience in HVAC maintenance in health-care facilities to list and evaluate the risk of each maintenance issue caused by a design defect, supported by the literature.

Following semistructured interviews with experts, 41 maintenance issues were identified as the most encountered issues. Subsequently, a survey was conducted in which 44 participants evaluated the probability and impact of each design-caused issue.

Chillers were identified as the HVAC components most prone to design defects and cost impact. However, air distribution ducts and air handling units are the most critical HVAC components for maintaining healthy conditions inside health-care facilities.

The unavailability of comprehensive data on the cost impacts of all design-related defects from multiple health-care facilities limits the ability of HVAC designers to furnish case studies and quantitative approaches.

This study helps HVAC designers acquire prior knowledge of decisions that may have led to unnecessary and avoidable maintenance. These design-related maintenance issues may cause unfavorable health and cost consequences.

The purpose of this study is to investigate and analyse the potential of existing buildings in the UK to contribute to the net-zero emissions target. Specifically, it aims to address the significant emissions from building fabrics which pose a threat to achieving these targets if not properly addressed.

The study, based on a literature review and ten (10) case studies, explored five investigative approaches for evaluating building fabric: thermal imaging, in situ U-value testing, airtightness testing, energy assessment and condensation risk analysis. Cross-case analysis was used to evaluate both case studies using each approach. These methodologies were pivotal in assessing buildings’ existing condition and energy consumption and contributing to the UK’s net-zero ambitions.

Findings reveal that incorporating the earlier approaches into the building fabric showed great benefits. Significant temperature regulation issues were identified, energy consumption decreased by 15% after improvements, poor insulation and artistry quality affected the U-values of buildings. Implementing retrofits such as solar panels, air vents, insulation, heat recovery and air-sourced heat pumps significantly improved thermal performance while reducing energy consumption. Pulse technology proved effective in measuring airtightness, even in extremely airtight houses, and high airflow and moisture management were essential in preserving historic building fabric.

The research stresses the need to understand investigative approaches’ strengths, limitations and synergies for cost-effective energy performance strategies. It emphasizes the urgency of eliminating carbon dioxide (CO₂) and greenhouse gas emissions to combat global warming and meet the 1.5° C threshold.

Research on online user privacy shows that empirical evidence on how privacy literacy relates to users' information privacy empowerment is missing. To fill this gap, this paper investigated the respective influence of two primary dimensions of online privacy literacy – namely declarative and procedural knowledge – on online users' information privacy empowerment.

An empirical analysis is conducted using a dataset collected in Europe. This survey was conducted in 2019 among 27,524 representative respondents of the European population.

The main results show that users' procedural knowledge is positively linked to users' privacy empowerment. The relationship between users' declarative knowledge and users' privacy empowerment is partially supported. While greater awareness about firms and organizations practices in terms of data collections and further uses conditions was found to be significantly associated with increased users' privacy empowerment, unpredictably, results revealed that the awareness about the GDPR and user’s privacy empowerment are negatively associated. The empirical findings reveal also that greater online privacy literacy is associated with heightened users' information privacy empowerment.

While few advanced studies made systematic efforts to measure changes occurred on websites since the GDPR enforcement, it remains unclear, however, how individuals perceive, understand and apply the GDPR rights/guarantees and their likelihood to strengthen users' information privacy control. Therefore, this paper contributes empirically to understanding how online users' privacy literacy shaped by both users' declarative and procedural knowledge is likely to affect users' information privacy empowerment. The study empirically investigates the effectiveness of the GDPR in raising users' information privacy empowerment from user-based perspective. Results stress the importance of greater transparency of data tracking and processing decisions made by online businesses and services to strengthen users' control over information privacy. Study findings also put emphasis on the crucial need for more educational efforts to raise users' awareness about the GDPR rights/guarantees related to data protection. Empirical findings also show that users who are more likely to adopt self-protective approaches to reinforce personal data privacy are more likely to perceive greater control over personal data. A broad implication of this finding for practitioners and E-businesses stresses the need for empowering users with adequate privacy protection tools to ensure more confidential transactions.

The purpose of this research is to ascertain the feasibility of fabricating polymer optical fibers (POFs) based textile structures by knitting with Polymethylmethacrylate (PMMA) based optical fibers for textile sensor application. It has long been established that by using the principles of physics, POFs have the capability to function as sensors, detecting strain, temperature and other variables. However, POF applications such as strain and pressure sensing using knitting techniques has since not been very successful due to a number of reasons. Commercially available PMMA-based optical fibers tend to be fragile and susceptible to breakages when subjected to stress during the knitting processes. Also light transmitted within these fibers is prone to leakage due to the curvature that results when optical fibers are interlaced or interlooped within fabric structures.

Using Stoll’s multi-gauge CMS 350 HP knitting machine, five fabric structures namely, 1 × 4 float knit structure, tunnel inlay knit structure, 3:1 fleece fabric and 2:1 fleece fabric structure respectively were used to knit sensor samples. The samples were subsequently tested for length of illumination and sensitivity relative to applied pressure.

The results of this preliminary study establish that embedding plastic optical fibers into a knitted structure during the fabric formation process for soft strain sensor application possible. The best illumination performance was recorded for tunnel inlay structure which had an average of 94 cm course length of POF being illuminated. Sensor sensitivity experiments also establish that the relative spectral intensity of the fiber is sensitive to both light and pressure. Problems encountered and recommendations for further research have also been discussed and proffered.

Due to resource limitations, an innovative technique (use of precision weight set) was used to apply pressure to the sensors. Consequently, information regarding the extent of corresponding sensor deformation has not been used in this initial analysis.

Because the fundamental step toward finding a solution to any engineering problem is the acquisition of reliable data, and considering the fact that most of the popular technologies used for soft textile sensors are still bedeviled with the problem of signal instability and noise, the success of this application thus has the tendency to promote the wide spread adoption of POF sensors for smart apparel applications.

As far as research on soft strain sensors is concerned, to the best of the authors’ knowledge, this is the first study to have attempted to knit deformable sensors using commercially available POFs.