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This paper aims to investigate the direct and combined impacts of entrepreneurial orientation (EO) and conservative orientation (CO) on perceived business performance (PBP) of small- and medium-sized enterprises (SMEs) under strategic-hybrid orientation (SHO) theory.

The data collected from the SABI NEO international database has 90 companies in 13 medium-to-high and high-tech activity sectors. The authors used partial least squares structural equation modelling to test the research model.

Business strategies match a SHO that includes both orientations, i.e. EO and CO. Moreover, as expected, the authors found evidence that each orientation produces performance-related sign-opposite significant impacts. Finally, the hypothesis regarding the positive synergistic effect of both orientations (EO and CO) on PBP was also supported.

One stems from the study’s cross-sectional nature, requiring a longitudinal approach. Another one resides in the absence of further examinations concerning multigroup analysis. Another restraint is the limitedness of data, focused on firms with med/high-tech intensity. For last, while the use of results in the initial stages of theory development can be beneficial, it is important to note that such results cannot be simply extrapolated or generalized to other industrial sectors without careful consideration of the contextual factors at play.

This study humbly endeavours to contribute to the finality of SMEs’ more steady and prosperous existence concerning the consciousness of the need to improve labour stability and wage fairness, conditions such as requiring a continuous commitment.

In this study, the authors aimed to investigate the impact of SHO on SMEs’ PBP. To this end, the authors simultaneously used two different strategic orientations (SOs): EO, which is widely studied in the literature, and CO, which has been less researched. The authors also examined their synergistic effects on PBP. The authors’ approach is based on Venkatraman’s strategic orientation of business enterprises model and the comparative paradigm of SOs.

This article examines the mechanisms through which big data analytics capabilities (BDAC) contribute to creating sustainable value and analyzes the mediating roles that supply chain management capabilities (SCMC), as well as circular economy practices (CEP), play through their impact on sustainable performance.

Following a literature review, a serial mediation model is presented. Hypotheses regarding direct and mediating relationships are tested to determine their potential for sustainability impact and circularity. Partial least squares structural equation modeling (PLS-SEM) has been applied for causal and predictive purposes.

The results indicate that big data analytics capabilities do not have a direct positive impact on sustainable performance but influence indirectly through SCMC and CEP.

Although some authors have addressed the associations between IT business value, supply chain (SC), and sustainability, this paper provides empirical evidence related to these relationships. Additionally, this study performs novel predictive analyses.

The purpose of this paper is twofold: firstly, to provide a measurement instrument for supply chain 4.0 ambidexterity by applying the theoretical perspective of ambidexterity to advance Industry 4.0; secondly, to empirically analyse how supply chain 4.0 ambidexterity and lean supply chain management contribute to enhancing the focal firm’s operational performance.

Empirical results are obtained through analysis of survey data from a sample of 209 Spanish focal firms in industrial sectors in an intermediate position in the supply chain. Structural equation modelling was performed to test the three proposed hypotheses.

Drawing on resource orchestration theory and the relational resource-based view, this study empirically demonstrates the full mediating role of lean supply chain management in the relationship between supply chain 4.0 ambidexterity and the focal firm’s operational performance.

Although recent research has highlighted the pertinence of applying inter-organisational ambidexterity to foster Industry 4.0 (Hofmann et al., 2019), to the best of the authors’ knowledge, this is one of the first studies to apply this theoretical framework to explain the transition to supply chain 4.0. In addition, to date, to the best of the authors’ knowledge, no study exists that has developed a measurement scale and used this concept in an empirical analysis to advance theory development.

The aim of this research is to analyze the knowledge transfer process in technological innovation clusters. The problem of the study addresses how organizations can act in a network to enhance experiences and gains, particularly in the aspect of knowledge management.

The study is qualitative, applied through a case study, cross-sectional and multiple sources of evidence – semistructured interviews, nonparticipant observation and analysis of documents and secondary institutional data. The case analyzed was the Technology Park of São José dos Campos, in Brazil, involving private companies, governmental organizations, universities and research institutions.

The results reinforce the arguments that the transfer of knowledge is influenced by factors, facilitators or inhibitors such as: cooperation, relationship with institutions, workforce mobility and geographical proximity, influencing the competitiveness and performance of the organizations in the cluster.

This study advances the knowledge management literature in network environments, especially in technological innovation clusters, systematizing and highlighting the facilitating and inhibiting dimensions of knowledge transfer.

The present work has a direct dialogue with the managers and actors involved in the governance of these organizational arrangements with regard to increasing the capacity for creation and the dissemination of knowledge among organizations, educational institutions, government and companies.

There is a presence of aspects indicating that knowledge goes beyond borders through dynamic and collaborative structures, reinforcing the premise that clusters must be perceived as an evolutionary system, whose result of interactions leads to a superior joint capacity.

Today’s society interest in mobile photography drives consumers’ and brands’ growing usage of Instagram. This paper aims to address the consequences of excessive use of Instagram on the negative feeling of losing information when not connected and the emotional fatigue resulting from an overcharge with new information. The mediating role of addiction between Instagram overuse and the two outcomes is also analyzed.

Data from 342 active Instagram users were used to test the proposed model, applying the partial least square equation modeling method (SmartPLS 3).

Addiction partially mediates the impact of overuse on emotional fatigue and instastress. Addiction to Instagram was mainly due to respondents’ lack of control over the time spent on it resulting in incapability to reduce its usage.

Social networking site managers, educators, families and public institutions should promote an adequate use of Instagram, making users (especially the young) aware of the potential threats of its excessive usage. The control on the amount of time devoted to Instagram is a key factor for detaining overuse and addiction, as well as avoiding the negative outcomes analyzed in this research.

The findings contribute to the extant knowledge on the negative side of the digitization of the individual, as little is known about it to the best of the authors’ knowledge.

La presente investigación aborda las consecuencias del uso excesivo de Instagram relacionadas con el sentimiento negativo de pérdida de información, cuando no se está conectado, y la fatiga emocional derivada de la sobrecarga de información. El estudio también analiza el papel mediador de la adicción entre el uso excesivo de Instagram y ambas consecuencias.

Para testar el modelo propuesto se utilizó información de 342 usuarios activos de Instagram, aplicándose el método de ecuaciones estructurales por mínimos cuadrados parciales (SmartPLS 3).

La adicción media parcialmente el impacto que el uso excesivo de Instagram tiene sobre (i) la fatiga emocional y (ii) el Instastress. La adicción a Instagram se deriva principalmente de la falta de control del tiempo invertido en su uso, lo que da como resultado su incapacidad para reducir dicho uso.

Los responsables de los medios sociales, los educadores, las familias y las instituciones públicas deberían promover un uso adecuado de Instagram, haciendo que los usuarios (especialmente los más jóvenes) sean conscientes de las amenazas potenciales de su uso excesivo. El control sobre la cantidad de tiempo dedicado a Instagram es un factor clave para detener el uso excesivo y la adicción, así como para evitar los resultados negativos analizados en esta investigación.

Los resultados contribuyen a ampliar el conocimiento sobre el lado negativo de la digitalización del individuo, dada la escasa literatura al respecto.

Adicción, Uso excesivo, Instastress, Fatiga emocional, Redes sociales, Instagram

Artículo de investigación

The purpose of this paper is to determine the drivers of the formation of e-loyalty in a tourist destination, providing a model composed of variables that are under the control of the firm along with others that are not fully controllable by professionals.

The study was carried out with a sample of 497 subjects, university students and online consumers, and with the use of structural equations (partial least squares).

Results show that young people give a high valuation to all the variables used in the research. These results contribute to the literature on e-loyalty in tourism destinations and improve tourism loyalty in this population segment.

The main limitation of this research has been related to the number of variables and measurement indicators that, according to the literature review, influence e-loyalty. Finally, a balanced and statistically significant model has been developed that has practical utility and analyzes online purchase of tourism products from a process perspective that includes variables that are internal and external to the firm.

The study suggests that young people have a favourable attitude and predisposition towards e-commerce, which, in turn, favours firms’ efforts to promote consumption and loyalty within the framework of the model’s variables.

This research paper has important value by analysing the initiating variables to determine how e-loyalty can be managed in tourist destinations, in addition to analysing an important segment for future tourism development.

To determine how to best deploy the Triple-A supply chain (SC) capabilities (AAA-agility, adaptability and alignment) to improve competitive advantage (CA) by identifying the Triple-A SC model with the highest CA predictive capability.

Assessment of in-sample and out-of-sample predictive capacity of Triple-A-CA models (considering AAA as individual constructs) to find which has the highest CA predictive capacity. BIC, BIC-Akaike weights and PLSpredict are used in a multi-country, multi-informant, multi-sector 304 plant sample.

Greater direct relationship model (DRM) in-sample and out-of-sample CA predictive capacity suggests DRM's greater likelihood of achieving a higher CA predictive capacity than mediated relationship model (MRM). So, DRM can be considered a benchmark for research/practice and the Triple-A SC capabilities as independent levers of performance/CA.

DRM emerges as a reference for analysing how to trigger the three Triple-A SC levers for better performance/CA predictive capacity. Therefore, MRM proposals should be compared to DRM to determine whether their performance is significantly better considering the study's aim.

Results with our sample justify how managers can suitably deploy the Triple-A SC capabilities to improve CA by implementing AAA as independent levers. Single capability deployment does not require levels to be reached in others.

First research considering Triple-A SC capability deployment to better improve performance/CA focusing on model's predictive capability (essential for decision-making), further highlighting the lack of theory and contrasted models for Lee's Triple-A framework.

The main objective of the study is to address the lack of sustainability assessments of smart connected health systems in the academic literature by presenting an assessment model to determine the alignment of these systems with the 17 Sustainable Development Goals (SDGs) proposed in the 2030 Agenda.

An evaluation model based on decision analysis is proposed that includes three phases: alignment framework, information gathering and assessment. This model measures the alignment of the connected health system with each of the 17 SDGs, identifying the goals and criteria associated with each SDG that the system achieves to satisfy.

The analysis reveals that the system has achieved more than 24% of the targets among the 17 SDGs. In addition, it identifies four sustainability challenges that the system potentially addresses in relation to the SDGs, providing valuable guidance for researchers and practitioners interested in sustainable health technology development.

The study's results have significant implications for policymakers and stakeholders in the health and technology sectors.

The originality of this study lies in its comprehensive approach to assessing the sustainability of connected health systems in the context of the SDGs, filling an important gap in the existing literature.

Drawing on resource and capability theory, this study aimed to analyze the relationship between the dynamic capabilities (DC), the knowledge management (KM) process (KMP) and results in customers and people. More specifically, the study argues that the KM process mediates the relationship between DC and the results outlined above. In addition, a predictive analysis is carried out that demonstrates the relevance of the KM process in the model.

The study sample is made up of 118 Spanish organizations that have some kind of recognition of excellence awarded by the European Foundation for Quality Management (EFQM). Partial least squares methodology is used to validate the research model, the hypothesis testing and the predictive analysis.

The results show that organizations which leverage the DC through the KMP improve customer and people outcomes. Moreover, the predictive power is higher when the KMPmediates the relationship between the DC and the results.

There is no consensus in the literature on the relationship between DC, KM and performance. Moreover, there are also not enough papers that study KM or DC through the dimensions that define these constructs or variables. Given this need, this work considers the KMP according to the stages of knowledge creation, storage, transfer and application. Similarly, DC is dimensioned in sensing, learning, integrating and coordinating capabilities. These, as reconfigurators of knowledge assets, influence the KMP. Accordingly, the empirical model connects these knowledge domains and analyses their link to outcomes.

Gastronomy can be a key destination choice factor. As tourists, people will be able to learn more about the culture of the place through its culinary assets. This paper aims to analyse the interest and the gastronomic motivations of tourists to the city of Granada (Spain), where two important UNESCO World Heritage Sites (WHS) are included.

To achieve the aim of this study, fieldwork was carried out on a representative sample of tourists in Granada (Spain). Specifically, a total of 1,612 valid surveys were filled out in culinary establishments and historical sites. In these surveys, the opinion of tourists regarding gastronomy and their motivations when travelling was assessed.

The results of this research allow to make a segmentation of tourists into three groups according to their position and their interest in gastronomy based on their destination choice, distinguishing among survivors, enjoyers and experiencers’ tourists. Additionally, it is confirmed that gastronomy is shaped as a motivation that influences the level of tourist satisfaction, performing as a differentiating element that can help increase the competitiveness of the destination.

This research contributes to the scarce academic literature on tourism experiences in a city with WHS recognitions. This study confirms the existence of a relationship between gastronomic motivations and the level of satisfaction achieved by tourists who visit the city of Granada, where no similar studies were found. In addition, this work confirms the connection between gastronomy and culture.