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Football exists and evolves in a dynamic ecosystem, displaying a massive and multidimensional influence on most contemporary societies, and football has grown into a significant industry with a plethora of stakeholders. This research is the first to comprehensively identify the key industry stakeholders and their distinct value, from the individual club perspective, and to conceptualise and test their interrelationship toward the development of a corresponding framework of club benefits.

The study applied a multilevel approach to collect and verify qualitative data. It initially developed a preliminary conceptual framework, which was first validated by an expert panel and was subsequently extensively tested in the Cyprus-specific context, which offered fertile ground for such a study. The empirical stage rested on 41 semi-structured, face-to-face interviews with very high-ranking individuals from the top nine football clubs, as well as with key industry stakeholders.

Though the examined industry is partly in line with international norms, it is also highly affected by unique characteristics that alter the various stakeholders' role, producing (even negative) value of varied typologies that is directly linked with the industry's financial, sporting, cultural and social conditions.

The research ultimately presents scholars, practitioners and policymakers with a systemic and comprehensive understanding of the individual club stakeholder value offerings, delivers a tested framework as a tool for social and business management and prescribes future avenues for research, governance and practice.

Extant studies on the subject are either partial or focus on individual stakeholders and evidently lack requisite scientific comprehensiveness. The current research bridges this significant gap in knowledge by exhaustively identifying the key industry stakeholders, explicating their relative social, economic or other value in the individual club perspective and developing a value-based stakeholder framework.

This paper aims to investigate how value drivers of internet medical business model affect value creation through a configurational approach. The internet medical business model (IMBM) is such a business model that integrates online and offline medical services with the driving force of internet technologies covering prediagnosis, in-diagnosis and postdiagnosis. The outbreak of COVID-19 and the support of national policies have boosted the development of internet health care. However, there are still many challenges in practice, such as the unclear innovation path, as well as difficulties in landing and profiting. Academic research has not yet provided sufficient theoretical insights. Therefore, to better explain and guide practice, it is urgent to clarify the innovation path and mechanism of value creation for IMBM.

Based on the sample of 58 internet medical firms in China, this paper adopts fuzzy-set qualitative comparative analysis (fsQCA) to explore the configurational effects of IMBM’s value drivers on value creation.

Building on the business model canvas and the characteristics of internet health care, five value drivers of IMBM are identified, namely, functional value proposition, emotional value proposition, user involvement, resource capabilities and connection properties. And the five value drivers form three configurations, which are, respectively, labeled as resource-driven configuration, user-operated configuration and product-combined configuration. From the perspective of the integration of traditional and emerging theories, such as resource-based view, internet economics and value cocreation, each configuration leads to value creation and improves value results with different mechanisms behind it.

First, combined with the business model canvas and the characteristics of internet health care, this paper identifies five value drivers of IMBM, thus improving the relevant research on internet health care. Second, based on the configurational effects, this paper discusses the mechanism behind the configurational effects of IMBM’s value drivers on value creation, thus expanding relevant research on the value creation of business models. Third, applying fsQCA and combining the advantages of qualitative research and quantitative research, this paper adds to the configurations of IMBM’s value drivers that achieve high-value results.

Absorptive capacity, technological collaboration and servitization are analyzed to establish ways to overcome the balance between products and services in manufacturing companies. A fresh perspective is introduced by presenting a framework for innovation strategy, moving beyond product-based R&D.

The hypotheses are tested using data on Spanish firms in the high-tech chemical and pharmaceutical industries through ordinary least squares regression analysis. The sample consists of 112 manufacturing firms included in the Spanish Survey of Business Strategies.

The results show that absorptive capacity facilitates servitization and that technological collaboration moderates the relationship between absorptive capacity and servitization. The synergies between absorptive capacity and technological collaboration for servitization are recognized from the perspective of open innovation as a way of resolving the trade-off between products and services.

Future research should introduce more sources of collaboration by broadening the value chain perspective. Other approaches to innovation may also be considered, including relationships to process innovation.

The results can provide meaningful guidance for companies to determine the key opportunities of servitization driven by absorptive capacity, and the best ways to leverage open innovation and collaboration strategies to exploit such approaches.

This research enriches theories on servitization, open innovation and innovative behavior. Open innovation strategy should be linked to greater servitization activity and should support an open service strategy. This approach is crucial for building innovation capabilities through technological collaboration.

This paper reports the results of research that examines the interrelationships between efficacy of sustainability values (SV) and pro-sustainable behaviors of potential tourists. A partially mediated model is postulated and tested to help explain additional error variance in predicting consumers’ destination choice decisions in tourism, hence voiding a critical research gap. Coined as the “environmentally intellectualist behavior,” a new mediator variable is tested to explain additional error variance in human-value models.

The study is based on data collected from two representative samples of potential tourists from the USA and Canada. Data analyses include exploratory and confirmatory factor analyses that were used to examine the underlying domain structures of SV, followed by a predictive model using structural equation modeling.

The study findings suggest that values are salient factors that underlie pro-sustainable tourism and travel behavior. Moreover, the results confirm the existence of a higher-order sustainability construct. The study contributes original insights to the field by demonstrating that there are direct and indirect positive relationships between SV, environmental behaviors and decisions of consumers who take a pro-sustainable stance when traveling.

By modeling values as antecedents to attitudes and testing interrelationships between SV and the mediator variables coined as the environmentally intellectual behavior, the authors developed and tested a predictive model to explain destination- and product choice decisions. The model tested herein advances the value theory in two fundamental ways: first, this study demonstrates that SV can be modeled as higher-order factors. Second, values are antecedents to attitude and other variables, therefore must be included in consumer behavior models. Finally, the culture or origin of tourists matters when examining the impact of values on tourists’ choice decisions. Political actions and environmental attitudes can be modeled as mediators to explain additional error variance.

Understanding the role of corporate strategies in sustainability has become a hot topic for scholarly research. Meanwhile, firms strive to innovate and shape their positive image in the contemporary business arena. Past research has ignored investigating whether and how sustainability-oriented corporate strategies could drive innovation and firm image among external stakeholders. To address the said research gap, this paper examines the path through which sustainability-oriented corporate strategy and environmental regulation improve green corporate image and green innovation capabilities (i.e. green process and product innovation).

This study adopted a quantitative survey-based method. The online survey was adopted to collect data from employees working at the managerial level in the equipment manufacturing sector. The data collected from 343 managers that was complete in all aspects was used for empirical analysis using structural equation modeling. Direct and indirect relations were evaluated.

The findings reveal that sustainability-oriented corporate strategy and environmental regulation drive green innovation and green corporate image. Findings further show that external knowledge adoption underpins these effects of sustainability-oriented corporate strategy and environmental regulation.

The study delivers theoretical and practical understandings of the importance of sustainability-oriented corporate strategies to green corporate image and green innovation capabilities.

This study aims to determine the barriers hindering the incorporation of blockchain technology (BCT) in two key service industries – hotel and health care – as well as to assess their readiness for implementing BCT after overcoming the barriers.

The barriers of this study are determined through two phases: a review of prior literature and obtaining expert opinions, which are then analyzed to identify specific barriers that are impeding the incorporation of BCT. Moreover, to generate a blockchain implementation reluctance index (BIRI), this study presents an interval-valued intuitionistic fuzzy set (IVIFS) that uses graph theory and matrix approach (GTMA). The permanent function in the GTMA approach is computed using the PERMAN algorithm. Finally, to compare the readiness of the hotel and health-care industries to adopt BCT, the BIRI values are plotted and evaluated.

The barriers identified by this study are listed under five major headings, namely, financial, operational, behavioral, technical and legal. This study revealed that the operational and technical barriers of BCT are critically hindering its widespread integration in hotel and health-care industries. Furthermore, on comparing the BIRI values of both industries, the result suggested that the hotel industry needs to work more on these barriers to effectively incorporate BCT. Besides the comparison, the BIRI values clearly indicate that both industries have to put a lot of effort into the mitigation of the barriers found by this study to successfully integrate BCT.

The experts’ opinions are used to evaluate the identified barriers, which raises the chance that the opinions are prejudiced based on the experts’ perspectives and ideologies. The sensitivity of decision-maker loads toward preference outcomes is not analyzed in this manuscript. Therefore, any recent sensitivity analysis may be considered a prospective field for future research. This study applies a multicriteria decision-making (MCDM) approach, IVIFS–GTMA, which limits the evaluation of the influence caused by individual barriers on the integration of BCT in the hotel and health-care industries. Henceforth, in future investigations, alternative MCDM methods may be used to analyze individual barriers.

According to the findings, if the hotel or health-care industry aims to incorporate BCT in its supply chain operations, it is recommended to emphasize more on the operational barriers along with the technical and behavioral barriers. The barriers mentioned in this manuscript can be used as guidance for developers in their development activities, such as scalability concerns, establishment costs, the 51% attack and the inefficient nature of BCT. Furthermore, they may address the potential users’ negative perceptions about security, privacy, trust and risk avoidance through creatively developed blockchain solutions to promote BCT implementation.

To the best of the author’s knowledge, this is the first study that identifies barriers toward BCT incorporation in the major service industries, i.e. hotel and health care. Moreover, this is the first study that compares the preparedness of the hotel and health-care industries to determine the industry that requires more work to implement BCT.

Promoting the adoption of digital payments by the elderly plays an important role in the development of the digital economy. The purpose of this study is to build an extended theory of planned behavior (TPB) model to predict the elderly's intention to pay for digital services under COVID-19 epidemic constraints.

Based on the extended TPB model, 320 qualified participants were recruited on the network. The structural equation model was tested using the SmartPLS3.3 tool, and the moderation effects were tested through SPSS26 and the Process macro.

The results showed that the three dimensions of TPB theory, the basic elements (perceived value and perceived risk), and the external environment (COVID-19 pandemic) were important factors that influence the elderly users' intention to adopt digital payments. Further research found that motivation factors (personal innovativeness, intergenerational support, and social support) can positively moderate these effects.

The results of the study provide a further explanation for understanding the willingness of elderly people to adopt digital payments during the COVID-19 pandemic and bring inspiration to system developers and social managers to reduce the risk of COVID-19 pandemic and increase the share of digital payments for this category.

This paper used the extended TPB theory to construct a fundamental environmental motivation (FEM) framework for understanding the main influencing factors of elderly users' intention to adopt digital payments during the COVID-19 pandemic.

Social media has the potential to enable exchange of diverse opinions, foster dialogue on important social issues and exert positive influence on stakeholders and society. However, evidence is contradictory as to whether this is the case; it is possible that millennials' behaviors on social media are mainly driven by conservation (conformity and safety) or self-enhancement (power and achievement). In this research, the authors examine the extent to which different human values (self-transcendence, conservation, self-enhancement and openness to change) influence millennials' activities and behaviors on social media.

The authors conduct three separate surveys on Facebook, Twitter and Instagram with 491 millennials (18–34 years of age) in the USA, examining the influence of four higher-order values of the Schwartz human values model (open self-transcendence, conservation, self-enhancement and openness to change) on specific social media activities (consumption, self-focused and sharing nonpersonal content activities).

First, the authors find that for millennial users, human values significantly influence social media activities. Second, conservation values, followed by self-enhancement values, overshadow the expression of open self-transcendence values on social media. Thus, social media platforms may function more as agents of conservation and self-enhancement than agents of personal growth.

This is among the first studies to examine the influence of human values on social media and to find that human values such as conservation and self-enhancement have a strong influence on users' social media activities, while open self-transcendence values, which lead to expansion and growth, do not find genuine expression on social media.

A shared cognitive schema is the fundamental source of tacit understanding within a team. This study aims to address how such a shared cognitive schema emerges and evolves in an interdisciplinary research team.

This study uses an exploratory single case study to analyze the emergence and evolution of a shared cognitive schema in an interdisciplinary research team systematically. The authors spent more than two years collecting data from the IAM team via semistructured interviews, archival data and observation. Subsequently, a framework for the resulting mechanism model was developed by analyzing the data using a three-step process.

This study shows that as the interdisciplinary research team develops, the shared cognitive schema passes through three stages: overlapping cognitive schema, complementary cognitive schema and synergetic cognitive schema. The mechanisms of overlap, complement and synergy play important roles. The convergent roles of partner-based recruiting, knowledge categorization and following the existing institution facilitate the overlapping of knowledge structures. Complementary cognitive schema sharing is facilitated by interdisciplinary member selection, knowledge stock expansion and the effects of accomplished mentors. The synergetic behaviors of group voice, interactive cognition and adaptive learning facilitate synergetic cognitive schema sharing.

This study is the first to discuss the emergence and evolution of a shared cognitive schema at the microlevel of knowledge structure and belief structure. It offers a new theoretical perspective on the development rules of scientific research teams and provides practical enlightenment regarding the establishment and operation of interdisciplinary research teams.

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

A new approach to gesture recognition using wearable devices.

This study has a broad application prospect in the field of human–computer interaction.

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.