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[EN] Review articles or literature reviews are a critical part of scientific research. While numerous guides on literature reviews exist, these are often limited to the philosophy of review procedures, protocols, and nomenclatures, triggering non-parsimonious reporting and confusion due to overlapping similarities. To address the aforementioned limitations, we adopt a pragmatic approach to demystify and shape the academic practice of conducting literature reviews. We concentrate on the types, focuses, considerations, methods, and contributions of literature reviews as independent, standalone studies. As such, our article serves as an overview that scholars can rely upon to navigate the fundamental elements of literature reviews as standalone and independent studies, without getting entangled in the complexities of review procedures, protocols, and nomenclatures., Open access funding provided by Libera Universita di Bolzano within the CRUI-CARE Agreement.

Purpose Technological advances in the last decade have caused both business and economic sectors to seek for new ways to adapt their business models to a connected data-centric era. Family businesses have also been forced to leave behind traditional strategies rooted in family stimuli and ties and to adapt their actions in digital environments. In this context, this study aims to identify major online marketing strategies, business models and technology applications developed to date by family firms. Methodology: Upon a systematic literature review, we develop a multiple correspondence analysis (MCA) under the homogeneity analysis of variance by means of alternating least squares (HOMALS) framework programmed in the R language. Based on the results, the analyzed contributions are visually analyzed in clusters.Design/methodology/approach Upon a systematic literature review, we develop an MCA under the HOMALS framework programmed in the R language. Based on the results, the analyzed contributions are visually analyzed in clusters.Findings Relevant indicators are identified for the successful development of digital family businesses classified in the following three categories: (1) digital business models, (2) digital marketing techniques and (3) technology applications. The first category consists of four digital business models: mobile marketing, e-commerce, cost per click, cost per mile and cost per acquisition. The second category includes six digital marketing techniques: search marketing (search engine optimization and search engine marketing (SEM) strategies), social media marketing, social ads, social selling, websites and online reputation optimization. Finally, the third category consists of the following aspects: digital innovation, digital tools, innovative marketing, knowledge discovery and online decision making. In addition, five research propositions are developed for further discussion and future research.Originality/value To the best of our knowledge, this study is the first to cover this research topic applying the emerging programming language R for the development of an MCA under the HOMALS framework.

In a digital ecosystem where large amounts of data related to user actions are generated every day, important concerns have emerged about the collection, management, and analysis of these data and, according, about user privacy. In recent years, users have been accustomed to organizing in and relying on digital communities to support and achieve their goals. In this context, the present study aims to identify the main privacy concerns in user communities on social media, and how these affect users’ online behavior. In order to better understand online communities in social networks, privacy concerns, and their connection to user behavior, we developed an innovative and original methodology that combines elements of machine learning as a technical contribution. First, a complex network visualization algorithm known as ForceAtlas2 was used through the open-source software Gephi to visually identify the nodes that form the main communities belonging to the sample of UGC collected from Twitter. Then, a sentiment analysis was applied with Textblob, an algorithm that works with machine learning on which experiments were developed with support vector classifier (SVC), multinomial naïve Bayes (MNB), logistic regression (LR), random forest, and classifier (RFC) under the theoretical frameworks of computer-aided text analysis (CATA) and natural language processing (NLP). As a result, a total of 11 user communities were identified: the positive protection software and cybersecurity and eCommerce, the negative privacy settings, personal information and social engineering, and the neutral privacy concerns, hacking, false information, impersonation and cookies data. The paper concludes with a discussion of the results and their relation to user behavior in digital environments and an outline valuable and practical insights into some techniques and challenges related to users’ personal data.

[EN] Peer-to-peer (P2P) lending uses two-sided platforms to link borrowers with a crowd of lenders. Despite considerable diversity in crowdlending research, studies in this area typically focus on several common research topics, including information asymmetries, social capital, communication channels, and rating-based models. This young research field is still expanding. However, its importance has increased considerably since 2018. This rise in importance suggests that P2P lending may offer a promising new scientific research field. This paper presents a bibliometric study based on keyword co-occurrence, author and reference co-citations, and bibliographic coupling. The paper thus maps the key features of P2P lending research. Although many of the most cited papers are purely financial, some focus on behavioral finance. The trend in this field is toward innovative finance based on new technologies. The conclusions of this study provide valuable insight for researchers, managers, and policymakers to understand the current and future status of this field. The variables that affect new financial contexts and the strategies that promote technology-based financial environments must be investigated in the future., Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.

PurposeThis paper aims to examine the effect of technological, organizational and environmental factors on the level of innovation outcomes in manufacturing small- and medium-sized enterprises (SMEs).Design/methodology/approachDrawing on the technology-organization-environment theory this paper conducts a discriminant analysis of firms’ innovation level based on a data set of manufacturing SMEs.FindingsThe results show that low- and high-innovative firms can be distinguished in terms of information technology (IT) knowledge and infrastructure, commitment-based human resources (HR) selection practices, exploitative innovation and organizational capital.Practical implicationsThe study findings support the idea that innovation is a complex phenomenon explained by multiple factors. As a consequence, firms need to devote extra efforts to develop IT knowledge and infrastructure, commitment-based HR selection practices and organizational capital because these are crucial for obtaining greater innovation outcomes. In addition, the identification of exploitative innovation as a strong discriminant variable highlights that the most effective way to be a highly innovative SME is through incremental innovation, which permits the firm to capitalize as much as possible on previous exploratory efforts.Originality/valueAlthough many studies have highlighted that innovation is more challenging for SMEs than for their larger counterparts, the vast majority of studies has been conducted in large companies. This paper extends prior literature by analyzing the discriminant variables that may distinguish between low- and high-innovative manufacturing SMEs.

The development of the Internet and the implementation of traditional marketing strategies have given rise to the emergence of digital marketing strategies exploited both by SMEs and large companie...

In recent years, the business ecosystem has focused on understanding new ways of automating, collecting, and analyzing data in order to improve products and business models. These actions allow operations management to improve prediction, value creation, optimization, and automatization. In this study, we develop a novel methodology based on data-mining techniques and apply it to identify insights regarding the characteristics of new business models in operations management. The data analyzed in the present study are user-generated content from Twitter. The results are validated using the methods based on Computer-Aided Text Analysis. Specifically, a sentimental analysis with TextBlob on which experiments are performed using vector classifier, multinomial naïve Bayes, logistic regression, and random forest classifier is used. Then, a Latent Dirichlet Allocation is applied to separate the sample into topics based on sentiments to calculate keyness and p-value. Finally, these results are analyzed with a textual analysis developed in Python. Based on the results, we identify 8 topics, of which 5 are positive (Automation, Data, Forecasting, Mobile accessibility and Employee experiences), 1 topic is negative (Intelligence Security), and 2 topics are neutral (Operational CRM, Digital teams). The paper concludes with a discussion of the main characteristics of the business models in the OM sector that use DDI. In addition, we formulate 26 research questions to be explored in future studies.

PurposeIn the last decade, the hospitality sector has undergone numerous changes in the organization and structure of its business models. Specifically, the adoption of new digital technologies has initiated transformative changes toward circular economy and sustainability. The present study aims to analyze whether the use of the digital reservation system in circular entrepreneurship businesses has an impact on entrepreneurs’ satisfaction and trust in the in circular economy.Design/methodology/approachThe data collected via a survey of 317 entrepreneurs who use a circular economy strategy were analyzed using SEM in a proposed model based on circular entrepreneurship businesses and the adoption of digital reservation systems.FindingsThe results showed a positive relationship between usability and perceived ease of use and user satisfaction and trust in using digital reservation systems to boost circular entrepreneurship in hospitality. Therefore, it was identified that adopting a digital reservation system can increase the efficiency of entrepreneur resources, as well as lead to creation of sustainable knowledge, augment the use of new sources of user information, improve prediction of services and demand and, consequently, boost sustainability and circular economy.Research limitations/implicationsFuture research can use the results of the present study to investigate how digital technologies work and affect user trust, satisfaction, and use of these systems in entrepreneurs’ projects in hospitality. In addition, it would be interesting to explore how these factors influence hospitality in different business models that support circular economy in tourism. To this end, researchers can use the variables used in the present study, along with other variables, to extend the proposed model and deepen the authors' research. In summary, this study contributes to the literature on the use of applications in hospitality sector and offer useful insight on how the adoption and use of new technologies can drive the management of knowledge and technology development, decision making and acquisition of new data sources that improve the experience of both entrepreneurs and users that interact with their services to enable circular entrepreneurship.Practical implicationsHospitality entrepreneurs can use the results of the present study to better evaluate how using these applications can affect the communication protocols with their employees and stakeholders. Furthermore, entrepreneurs operating in the hospitality sector can use the results to develop action plans focused on the circular economy, new knowledge creation, as well as development and adoption of new digital technologies that enable circular entrepreneurship. In this way, hospitality companies will be able to effectively combine both more traditional offline channels and new technologies, such as mobile applications or the Internet.Social implicationsThe authors' prediction of a strong positive link between perceived usefulness and user trust was also supported by the results of data analysis. The finding that perceived utility increases user trust in entrepreneurs when making adopting these technologies is also consistent with other similar studies. Finally, the results of this study also confirmed the hypothesized link between the perceived utility of digital technologies and user satisfaction. Taken together, the results also highlight the relevance of analyzing the use of digital reservation systems in the hospitality sector to enable circular entrepreneurship.Originality/valueTaken together, the results highlight the relevance of analyzing the use of digital reservation systems in the hospitality sector to enable circular entrepreneurship and increase the perceived usefulness of new digital technologies so that to improve sustainable actions and the circular economy globally.

The growing use of social networks has led to the emergence of ethical and privacy concerns regarding the management of user data and how social networks train algorithms for economic purposes to organize the content shown to users. In this context, the present study aims to define and identify (i) the main concepts and (ii) performance measurements that social networks use to increase user engagement and modify user online behavior from the perspective of ethical design and surveillance capitalism in social media. Since previous research on this issue is scarce, this study bridges this gap in the literature by developing a Systematic Literature Review (SLR) of major scientific contributions made so far in this research area. We identify a total of 10 performance measurements and 4 ethical design measurements used by social media companies to increase user engagement and to achieve user behavior modification online, at times without users’ awareness about this effect. Furthermore, we critically analyze the identified 14 indicators, as previous research suggests that these indicators can generate addiction and modification of user behavior and feelings. The paper concludes with a discussion of important theoretical and practical implications of ethical design in social media for further research; we also question the economic approaches proposed in the business models of digital and social media platforms.

[EN] The present study aimed to analyse the main risks related to security and privacy of social networks based information systems in Industry 4.0. The methodology we used is an innovative exploratory data-driven process divided into three steps. First, we performed sentiment analysis to divide the database composed of 67, 206 tweets into feelings. Second, we applied a topic-modelling algorithm to extract topics. Third, we applied textual analysis to collect insights. A total of 10 topics related to security and privacy issues were identified as results. The paper concludes with a discussion of the challenges and main concerns related to the identified topics., In gratitude to the Ministry of Science, Innovation and Universities and the European Regional Development Fund: RTI2018-096295-B-C22

[EN] The definition and measurement of digital skills and competences needed to succeed in the 21st century context has been a widely researched topic within the last years. Academics and professionals consider that it has an increasing importance due to the process of digital transformation in which the organisations and society are immersed, which is pushing to achieve a knowledge society. For these reasons, a bibliometric analysis of the topic plays a key role to have a big picture of the conducted research since the date and establish key countries, authors and journals which lead the investigation on the topic. Moreover, the analysis of the knowledge frontier and research gaps has discovered the stage in which this research line is situated and the needs for the establishment of future research guidelines

[EN] Based on organizational information processing theory (OIPT), this study examines how and when business networks exert a positive influence on firms' organizational resilience capacity. Using data collected from 409 Chinese manufacturing firms during the COVID-19 pandemic, and by disaggregating business networks into two dimensions-network breadth and network depth-our findings show, firstly, that both network breadth and network depth are positively correlated to the organizational resilience capacity of firms; secondly, that these relationships are mediated by firms' ambidextrous learning; and thirdly, that the positive effects of network breadth and network depth on organizational resilience capacity are stronger when the firms' digital technology levels are higher. Furthermore, through additional analysis, we find that the positive impact of business networks on organizational resilience capacity is stronger for non-state-owned enterprises (non-SOEs) than it is for SOEs, and also that the moderating effect of digital technology on the relationship between business networks and organizational resilience capacity is greater for non-SOEs than it is for SOEs. These findings provide new insight into how a firm's business network, in combination with its ambidextrous learning and level of digital technology, affects its organizational resilience capacity development, which helps it survive a crisis for future sustainable development., This research was supported by the National Natural Science Foundation of China (Grant number: 71922016; 71772118), and Major Project of National Social Science Fund of China (Grant number: 20&ZD059).

In recent decades, low-cost airlines have proliferated in the European market offering cheap tickets and increasing popularity. This business model, characterised by cost leadership, has been studied on numerous occasions. The case of the Irish airline Ryanair has presented different challenges over the last few years in relation to its stakeholders, who are shaping the sustainability of the current era of air travel. This business model should be adapted to the current demands of the market, such as corporate social responsibility or care for the environment. The functioning of low-cost airlines regarding the use they make of ERP management systems is also analysed. They aim to balance their cost strategy with the development of internal resources and capabilities for the company's long-term strategy. A major current challenge for low-cost airlines is the implementation of ERP management systems to make strategies oriented to the customer, sustainability, and corporate social responsibility.

Technological development of the last several decades has driven open innovation towards organizational, business, social, and economic change. Open innovation has emerged as the main driver of change in a business sector that needs to be flexible and resilient, rapidly adapting to change through innovation. In this context, the present study aimed to explore the limits of open innovation by extracting evidence from user-generated content (UGC) on Twitter using social media mining. To this end, in terms of the methodology, we first applied machine learning Sentiment Analysis algorithm texted using Support Vector Classifier, Multinomial Naïve Bayes, Logistic Regression, and Random Forest Classifier to divide the sample of n = 586.348 tweets into three groups expressing the following three sentiments: positive, negative, and neutral. Then, we used a mathematical topic modeling algorithm known as Latent Dirichlet allocation to analyze the tweet databases. Finally, Python was used to develop textual analysis techniques under the theoretical framework of Computer-Aided Text Analysis and Natural Language Processing. The results revealed that, in the tweets dataset, there were eight topics. Of these topics, two contained tweets expressing negative sentiments (Culture and Business Models/Management), three topics contained tweets expressing positive sentiments (Communities, Creative projects and Ideas), and three topics contained tweets expressing neutral sentiments (Entrepreneurship, Teams and Technology). These topics are discussed in the context of limitations, risks, and characteristics of open innovation according to the UGC on Twitter. The paper concludes with the formulation of 20 limits of open innovation and 27 research questions for further research on open innovation, as well as a discussion of theoretical and practical implications of the study. UGCUser-Generated ContentUGDUser-Generated DataCATAComputer-Aided Text AnalysisNLPNatural Language ProcessingLDALatent Dirichlet AllocationSVCSupport Vector ClassifierMNBMultinomial Naïve BayesLRLogistic RegressionRFCRandom Forest Classifier

[EN] In today's global culture where the Internet has established itself as the main tool for communication and commerce, the capability to massively analyze and predict citizens' behavior has become a priority for governments in terms of collective intelligence and security. At the same time, in the context of novel possibilities that artificial intelligence (AI) brings to governments in terms of understanding and developing collective behavior analysis, important concerns related to citizens' privacy have emerged. In order to identify the main uses that governments make of AI and to define citizens' concerns about their privacy, in the present study, we undertook a systematic review of the literature, conducted in-depth interviews, and applied data-mining techniques. Based on our results, we classified and discussed the risks to citizens' privacy according to the types of AI strategies used by governments that may affect collective behavior and cause massive behavior modification. Our results revealed 11 uses of AI strategies used by the government to improve their interaction with citizens, organizations in cities, services provided by public institutions or the economy, among other areas. In relation to citizens' privacy when AI is used by governments, we identified 8 topics related to human behavior predictions, intelligence decision making, decision automation, digital surveillance, data privacy law and regulation, and the risk of behavior modification. The paper concludes with a discussion of the development of regulations focused on the ethical design of citizen data collection, where implications for governments are presented aimed at regulating security, ethics, and data privacy. Additionally, we propose a research agenda composed by 16 research questions to be investigated in further research., In gratitude to the Ministry of Science, Innovation and Universities and the European Regional Development. Fund: RTI2018-096295-BC22.

PurposeThis study contributes to the limited literature on crowdlending by providing a data-driven analysis of the sector. A synthetic DP2 indicator is proposed to identify the leaders of the crowdlending market, the key factors behind their success and the medium-term competitive implications.Design/methodology/approachThe study examines 17 crowdlending platforms and eight performance indicators. The information provided by these indicators is aggregated using a synthetic indicator based on theP2Distance (DP2) method.FindingsMintos, Evoestate, Peerberry, Bondster and Fellow Finance are the leading platforms. This method reveals the key variables in the identification of market leaders, namely year-on-year variation in the number of investors and year-on-year variation in lending per investor. The leaders in terms of lending volumes should not take their current situation for granted. Small and medium-sized platforms are pushing hard and may overtake the incumbents as market leaders.Practical implicationsFinancial intermediation through crowdlending is becoming an increasingly popular alternative to traditional models. Changes in the sector are expected in the coming years due to the rise of platforms with a moderate amount of lending and solid year-on-year improvement. To become leaders and to attract both lenders and borrowers, platforms are encouraged to improve the information that they provide.Originality/valueThis paper offers the first analysis of market leadership in the crowdlending sector. It analyses the competitive market of the crowdlending sector based on its actors and key factors. These factors explain the differences in the market position of different platforms. Based on this analysis, the trends in this sector can be identified. This study is exploratory, so it offers empirical data that can be useful in the development of theories that apply to the sector.

In the global and turbulent world we live in, companies must differentiate themselves by creating a competitive advantage through constant innovation to adapt to the changing environment. A firm's competitive advantage is permanently being contested. Thus, preserving this competitive advantage is critical. Consequently, firms can innovate to survive and thrive through two mechanisms: crowdsourcing and online social networks. However, the interrelationships between these mechanisms are poorly understood and need further testing. Online social networks and crowdsourcing involve individuals who are encouraged to share ideas, driving innovation through knowledge provision. This study aims to determine the importance of online social networks and crowdsourcing as elements that favor organizational learning processes to promote organizational development. This paper presents a set of hypotheses on the relationships between these variables. The findings suggest that online social networks, crowdsourcing, and organizational performance are correlated. Therefore, both of the research hypotheses are supported. Online social networks are shown to play an important role in companies by positively influencing the performance of organizations. Similarly, crowdsourcing is shown to benefit organizational performance.

[EN] Lack of trust, lack of references and the confidential nature of cybersecurity projects make internationalization in companies from the cybersecurity sector a great challenge. The development of lean methodologies over recent years has presented a method to reduce time and effort, measure performance in each step and pivot when it is necessary to apply a process to a different field. Considering that internationalization resembles entrepreneurship, because of uncertainty and risk in a new market where the value proposition should be validated, the Lean Start-up philosophy will serve as a theoretical framework in which to operate. The study of international challenges of cybersecurity companies and elaboration of an 'eight-step' internationalization mechanism based on Lean Start-up methodology will imply a cost-effective solution for cybersecurity enterprises that want to achieve profitability and higher return on investment in internationalization., [ES] La falta de confianza, la falta de referencias previas y la naturaleza confidencial de los proyectos de ciberseguridad hacen que la internacionalización de las empresas del sector sea un gran desafío. El desarrollo de metodologías lean en los últimos anos ¿ ha presentado un método para reducir el tiempo y el esfuerzo en el proceso de internacionalización y permitir medir el rendimiento en cada paso y pivotar cuando sea necesario. Teniendo en cuenta que la internacionalización se asemeja a la iniciativa empresarial, debido a la incertidumbre y el riesgo en un nuevo mercado donde se debe validar la propuesta de valor, la filosofía Lean Start-up servirá como marco teórico en el que operar. El estudio de los desafíos internacionales de las empresas de ciberseguridad y la elaboración de un mecanismo de internacionalización de ocho pasos basado en la metodología Lean Start-up implicará una solución rentable para las empresas de ciberseguridad que desean lograr rentabilidad y un mayor retorno de la inversión en internacionalización.

[EN] The new business challenges in the B2B sector are determined by connected ecosystems, where data-driven decision making is crucial for successful strategies. At the same time, the use of digital marketing as a communication and sales channel has led to the need and use of Customer Relationship Management (CRM) systems to correctly manage company information. The understanding of B2B traditional Marketing strategies that use CRMs that work with Artificial Intelligence (AI) has been studied, however, research focused on the understanding and application of these technologies in B2B digital marketing is scarce. To cover this gap in the literature, this study develops a literature review on the main academic contributions in this area. To visualize the outcomes of the literature review, the results are then analyzed using a statistical approach known as Multiple Correspondence Analysis (MCA) under the homogeneity analysis of variance by means of alternating least squares (HOMALS) framework programmed in the R language. The research results classify the types of CRMs and their typologies and explore the main techniques and uses of AI-based CRMs in B2B digital marketing. In addition, a discussion, directions and propositions for future research are presented., In gratitude to the Ministry of Science, Innovation and Universities and the European Regional Development Fund: RTI2018-096295-BC22.

Although digitalization is a reality for companies and contributes to value creation, few studies have examined its impact on business performance in the service sector. The aim of this paper is to analyze how the digitalization of knowledge-intensive business services (KIBS) contributes to their performance. The analysis centers on their use of information systems, as well as the contingent factors of the manager’s age and gender and company size. This study explores how these factors contribute to the performance of KIBS, with performance here measured in terms of future financial performance. The analysis was conducted using fuzzy-set qualitative comparative analysis (fsQCA). The study shows that updating social networks, using social networks for corporate purposes, having a high level of training in digital tools, and having older managers can enhance company performance.

Facing global climate change challenges entails a sustainable development of transportation. Governments and automobile manufacturers are highly aware of how a large-scale deployment of Electric Vehicles (EVs) can reduce greenhouse gas (GHG) emissions and mitigate global warming. This study aids the design of the adaptation strategies of the automotive industry to meet global goals on climate change by means of a fuzzy-set qualitative comparative analysis (fsQCA), which makes it possible to measure the level of actors’ satisfaction. This allows identification of a combination of factors leading to the outcome while dealing with uncertain environments due to the heterogeneous nature of actors with conflicting of interests. The methodology has been successfully applied to a case study, thus providing greater transparency, fairness, social equity, and consensus among actors.

[EN] In present-day in consumers' homes, there are millions of Internet-connected devices that are known to jointly represent the Internet of Things (IoT). The development of the IoT industry has led to the emergence of connected devices and home assistants that create smart living environments. However, the continuously generated data accumulated by these connected devices create security issues and raise user's privacy concerns. The present study aims to explore the main security issues in smart living environments using data mining techniques. To this end, we applied a three-sentence data mining analysis of 9,38,258 tweets collected from Twitter under the user-generated data (UGD) framework. First, sentiment analysis was applied using Textblob which was tested with support vector classifier, multinomial naive bayes, logistic regression, and random forest classifier; as a result, the analyzed tweets were divided into those expressing positive, negative, and neutral sentiment. Next, a Latent Dirichlet Allocation (LDA) algorithm was applied to divide the sample into topics related to security issues in smart living environments. Finally, the insights were extracted by applying a textual analysis process in Python validated with the analysis of frequency and weighted percentage variables and calculating the statistical measure known as mutual information (MI) to analyze the identified n-grams (unigrams and bigrams). As a result of the research 10 topics were identified in which we found that the main security issues are malware, cybersecurity attacks, data storing vulnerabilities, the use of testing software in IoT, and possible leaks due to the lack of user experience. We discussed different circumstances and causes that may affect user security and privacy when using IoT devices and emphasized the importance of UGC in the processing of personal data of IoT device users., In gratitude to the Ministry of Science, Innovation and Universities, Spain and the European Regional Development Fund: RTI2018-096295-B-C22.

Crowdlending platforms are becoming increasingly important as a collective financing mechanism for entrepreneurs and small and medium-sized enterprises (SMEs), especially those at an early stage. This study, which is based on a survey of investors on a Spanish crowdlending platform, uses fuzzy-set qualitative comparative analysis (fsQCA) to examine investor satisfaction with crowdlending platforms. Specifically, the study examines communication policies and the quality of the investor experience based on the information provided by these platforms. The value of this article lies in its examination of the antecedents of crowdlending investor satisfaction. The analysis shows that the actions of ensuring that it is easy to browse the platform, frequently updating project details, offering a mobile application, publishing a blog with details of new developments and frequently sending investors emails with information to support their investment decisions increase investors’ satisfaction with crowdlending platforms.

[EN] In this paper, the resource-based view is used to analyze the implementation of crowdsourcing as an IT-based practice. The study examines strategic positioning regarding market orientation and the role of two capabilities: transformational leadership and organizational learning capability, in the implementation of crowdsourcing. An empirical study of Spanish telecommunications and biotechnology companies confirms the moderating effect of these capabilities on the relationship between market orientation and crowdsourcing.

[EN] Within organisational analysis, a concept that has been gaining importance has been organisational ambidexterity, where two factors play an important role: entrepreneurial intensity and innovations. The objective of this article is to analyse the relationship between entrepreneurial intensity and ambidexterity. The conceptualisation of ambidexterity distinguishes between ambidextrous activities and ambidextrous outcomes. To carry out this objective, we have tested several theoretical relationships. We have used partial least squares methodology to develop an empirical study in 25 European countries. Results confirm that collaboration networks have a positive effect on entrepreneurship intensity. This effect is greater than the one obtained by ambidextrous activities or new technologies. We also show that entrepreneurship intensity has a mediating role between ambidextrous activities and ambidextrous outcomes.

[EN] The globalization of tourism has recently increased the importance of foreign demand for most European destinations. Hotel chains have been long investigated from several perspectives. However, no research has verified the alleged ability of chains to attract foreign demand, while this information is highly sought after by hotel investors and owners when evaluating affiliation opportunities. The present study covers Italy. It is based on a survey of 148 branded hotels for 21 destinations and 22 brands. Adopting a new metric to compare the ability of hotels to sell abroad (Foreign market Per Available Room; FmPAR), it has been found that chain-affiliated hotels perform better than independent hotels in attracting foreign demand. This is particularly true for international chains compared to domestic ones. On the other hand, the effect is stronger in three-star hotels than in four and five-star ones, in destinations where chain penetration is low.

[EN] The world today is constantly changing and evolving. The industry 4.0 revolution, digitisation, the arrival of the Internet of Things and the global health emergency caused by the Covid-19 crisis, are factors that have made companies have to adapt their business models and forms working to this new reality. For this reason, the need for improvement and adaptation of skills of employees and organisational capabilities is no longer a competitive advantage but necessary to survive. Digital competences, 21st century skills and digital leadership are concepts that have been widely studied theoretically in the last ten years. In addition, some empirical studies have established causal hypotheses between factors related to the skills of employees and company variables. Resilience, organisational learning capacity, agility, work engagement and motivation are the key factors that companies must promote and ensure among their employees for a correct evolution and adaptation to this new global situation.

Purpose There is a growing research interest in the relationships between networks and the firm’s assets and between networks and innovation. Studies have shown the complexity and idiosyncrasies of these relationships for firms in clusters. The way firms in clusters build certain organizational resources and capabilities, however, remains underexplored. Based on the assumption that most of these organizational assets rely on human resources, the purpose of this paper is to shed light on the mechanisms through which a set of managerial practices (the human resource management (HRM) system) enhances innovation. Design/methodology/approach Micro-level data were collected for 139 firms located in three Spanish industrial clusters. Next, the main constructs were developed. A multiple mediator model was then used to examine how HRM systems influence innovation through strategic vision, embeddedness in local networks, the implementation of enterprise systems, and cluster characteristics. Findings The effect of HRM systems on innovation performance was indirect rather than direct. All four mediating variables included in the model were found to be relevant mechanisms through which HRM systems affect innovation performance. The statistical significance of these variables, however, varied depending on the type of innovation (product, process, organizational, or marketing). Practical implications Greater attention should be paid to the structure and sophistication of HRM systems. Top-level managers should be aware of the linkages between HRM systems and mediators. Greater human resource orientation in strategic planning, enterprise system design, and networking practices reinforces the association between HRM systems and innovation. Originality/value This study advances our understanding of the mechanisms underlying the relationship between HRM systems and innovation. From an academic perspective, this study enriches the cluster literature by better integrating human resources with innovation processes. Furthermore, this study creates research opportunities by disentangling the role of different managerial practices and refining the operationalization of the mediating variables. The findings can also help managers develop human resources and innovation strategies.

In recent years, strategies focused on data-driven innovation (DDI) have led to the emergence and development of new products and business models in the digital market. However, these advances have given rise to the development of sophisticated strategies for data management, predicting user behavior, or analyzing their actions. Accordingly, the large-scale analysis of user-generated data (UGD) has led to the emergence of user privacy concerns about how companies manage user data. Although there are some studies on data security, privacy protection, and data-driven strategies, a systematic review on the subject that would focus on both UGD and DDI as main concepts is lacking. Therefore, the present study aims to provide a comprehensive understanding of the main challenges related to user privacy that affect DDI. The methodology used in the present study unfolds in the following three phases; (i) a systematic literature review (SLR); (ii) in-depth interviews framed in the perspectives of UGD and DDI on user privacy concerns, and finally, (iii) topic-modeling using a Latent Dirichlet allocation (LDA) model to extract insights related to the object of study. Based on the results, we identify 14 topics related to the study of DDI and UGD strategies. In addition, 14 future research questions and 7 research propositions are presented that should be consider for the study of UGD, DDI and user privacy in digital markets. The paper concludes with an important discussion regarding the role of user privacy in DDI in digital markets.

[EN] The social Internet of Things (SIoT) shares large amounts of data that are then processed by other Internet of Thing (IoT) devices, which results in the generation, collection, and treatment of databases to be analyzed afterwards with Big Data techniques. This paradigm has given rise to users' concerns about their privacy, particularly with regard to whether users have to use a smart handling (self-establishment and self-management) in order to correctly install the SIoT, ensuring the privacy of the SIot-generated content and data. In this context, the present study aims to identify and explore the main perspectives that define user privacy in the SIoT; our ultimate goal is to accumulate new knowledge on the adoption and use of the concept of privacy "by default" in the scientific literature. To this end, we undertake a literature review of the main contributions on the topic of privacy in SIoT and Big Data processing. Based on the results, we formulate the following five areas of application of SIoT, including 29 key points relative to the concept of privacy "by default": (i) SIoT data collection and privacy; (ii) SIoT security; (iii) threats for SIoT devices; (iv) SIoT devices mandatory functions; and (v) SIoT and Big Data processing and analytics. In addition, we outline six research propositions and discuss six challenges for the SIoT industry. The results are theorized for the future development of research on SIoT privacy by "default" and Big Data processing., In gratitude to the Ministry of Science, Innovation and Uni-versities and the European Regional Development Fund: RTI2018-096295-B-C22.

One of the current problems of the entrepreneurial world is the successful implementation of the Balanced Scorecard (BSC), which is why it is interesting to study the variables that can influence its application in business. The main purpose of this paper is to establish a theoretical model through the literature review, that should consider the relationship between the transformational leadership among company staff (Avolio, Bass and Jung, 1999) and the empowerment of the rest of employees (Thomas and Velthouse, 1990 Spritzer, 1995) upon the achievement of an increased capacity for organizational learning in the implementation of the BSC in companies (Easterby-Smith & Araujo,1999) from the following perspectives: financial, customer, business process, learning and growth in major companies in the hotel sector, specifically in four and five-star hotels.The Balanced Scorecard (BSC) is a strategic management model (Norton & Kaplan, 1992) that allows the measurement and control of the tangible and intangible objectives based on the company´s mission and vision statements. The implementation of BSC has a great influence on the predisposition, training and motivation in middle as well as executive management through empowerment and leadership, hence the importance of the analysis of these variables by means of the BSC.

Social economy is considered as the option that offers the best response in times of crisis. In this context, social economy companies play an essential role in the promotion of sustainable growth. This research wants to present the importance of social entrepreneurship in the organizational performance of a company. It also aims to show the positive relationship between the extent to which social entrepreneurship is implemented and the creation of distinctive marketing competences, as well as the mediating role these competences have between social entrepreneurship and organizational performance. For this purpose, an analysis of 221 Spanish social-economic entities has been developed from January to May 2014. In order to evaluate organizational performance, a validated scale has been used (Nakata, 2008), since it integrates sociometric characteristics that are necessary for this research. For the two remaining constructs, that is to say, social entrepreneurship and distinctive marketing competences, specific items have been developed by taking into consideration the analysis of their sociometric properties that could lead to the validation of the relationship among the three proposed variables. The results show a positive relationship between the extent to which an organization introduces social entrepreneurship and its organizational performance, social entrepreneurship and the creation of distinctive marketing competences, as well as the influence of distinctive marketing competences as a mediating variable in the relationship between the degree of implementation of social entrepreneurship and organizational performance.

[EN] The aim of this paper is to examine the relationship between external cooperation and entrepreneurial orientation (EO). This relationship is explored in cluster environment, wherein entrepreneurial organizations compete and cooperate simultaneously to pursue opportunities. The following hypothesis is tested: External cooperation is positively correlated with entrepreneurial orientation. The hypothesis is tested with a correlation analysis on a sample of 77 small-sized enterprises operating in the Malopolska region in Poland, wherein several clusters are active. Additionally, the regression analysis is conducted to examine the associations between inter-organizational cooperation and EO dimensions. The findings confirm that external cooperation is positively correlated with EO. This observation is confronted with a pro-competitive approach that is a constitutional element of the entrepreneurship concept. Moreover, the findings show that the correlation between external cooperation and a firm's performance is stronger than between some other EO dimensions and performance. Additionally, the findings show the important role of relationships between organizations and their clients. In the paper, several remarks for development of the theory are discussed, including the need for incorporating inter-organizational cooperation into a set of entrepreneurial traits and reflecting it in entrepreneurial orientation scales. The findings confirm the importance of that direction of theory development that focuses on inter-organizational collaboration in the context of entrepreneurship., This research was funded by the Faculty of Management of AGH University of Science and Technology in Krakow with financial support of Ministry of Science and Higher Education of Republic of Poland [project no. 11/11.200.321]

[EN] Since the end of the 1990s, the number of articles on coopetitiona relationship built on simultaneous competition and cooperationhas steadily increased in response to the growing prevalence of relationships of coopetition in many industries. The tension inherent in a relationship of coopetition with a direct competitor presents both a challenge for managers and, at the same time, an exciting and complex research area. Different researchers of coopetition have addressed the topic from vastly different perspectives, basing their research on different theoretical frameworks, types of analysis, methods, and aims. By classifying articles on coopetition published in the last 20years, this paper presents an application of cluster analysis to examine trends and tendencies in coopetition research. The paper also assesses whether this research field has followed a coherent progression during this period. The research reveals two independent research trends within the coopetition literature. The first research trend consists of studies that have mathematically modeled and simulated coopetition scenarios using game theory, whereas the second research stream consists of theoretical research describing the dynamics and tensions of coopetition based on evidence from case studies. Based on the cluster analysis, inter-firm alliances and their governance mechanisms emerge as the most promising theoretical and practical approach to improve cooperation between competitors.