Search results

This study aims to develop and test a conceptual model of business students' intention to establish a start-up business that involves attitude, perceived behavioral control (PBC), entrepreneurial competence, financial access, lecture service quality, curriculum program, extracurricular activity and institutional support simultaneously.

An online survey was performed. The respondents were 196 business students in a private university in Indonesia. The data were analyzed using partial least square structural equation modeling (PLS-SEM).

Business students' intention to establish a start-up business was positively and significantly influenced by attitude and PBC. PBC was positively and significantly influenced by entrepreneurial competence and financial access. Attitude and entrepreneurial competence were positively and significantly influenced by curriculum program and extracurricular activity, but not influenced by lecture service quality and institutional support. Financial access was positively and significantly influenced by extracurricular activity and institutional support.

This research was conducted in a private university in Indonesia. Therefore, to test the stability of the research findings and the proposed conceptual model, it is necessary to conduct research in different contexts.

Research on the intention to establish a start-up business that simultaneously considers attitude, PBC, entrepreneurial competence, financial access, lecture service quality, curriculum program, extracurricular activity and institutional support is still scarce in the literature. This study addressed the gap.

This study aims to present an innovative sandbox platform that implements a decision support system (DSS) to assess the sustainable development goals (SDGs) addressed at the municipal level. It intends to determine the relative importance of each SDG in municipalities and explore the synergies that can be discovered among them.

Participatory action research is used to develop a DSS and an algorithm designated as discrete heavy fuzzy was also developed, which extends the Apriori algorithm to include discrete quantitative assessments of the level of SDG compliance by each project. A scenario consisting of three municipalities in Portugal (i.e. Porto, Loulé and Castelo de Vide) was chosen to demonstrate the implementation of the sandbox platform and to interpret the observed results.

The results reveal significant differences in the typology of SDGs addressed by each municipality. It was found that municipal sustainable projects are strongly influenced by the contextual factors of each municipality. Porto has projects that address the first five SDGs. Loulé appears projects that promote innovation, the fight against climate change and the development of sustainable cities. Castelo de Vida has initiatives related to innovation and infrastructure and decent work and economic growth.

This study provides knowledge about the relative importance of the SDGs in Portuguese municipalities and explores the synergies among them. The proposed sandbox platform fills the gaps of the ODSlocal Webtool by proposing a dynamic and interactive approach for the exploration of quantitative indicators regarding the implementation status of the SDGs established in the 2030 Agenda.

This study provides knowledge about the relative importance of the SDGs and the various synergies that exist between them considering the Portuguese municipalities. The sandbox platform presented and developed within this study allows filling the gaps of the ODSlocal Webtool that gathers essentially qualitative information about each project and offers a dynamic and interactive exploration with quantitative indicators of the implementation status of the SDGs established in the 2030 Agenda.

This conceptual paper aims to develop the vision of a novel policy tool called the digital industrial cluster (DIC) thought for a future context shaped by digital economies and Industry 4.0. The DIC departs from the industrial cluster’s precepts and take them into the digital agglomeration phenomenon.

This research uses a discursive and theoretical approach. To create a clear picture related to the research topic, this paper reviews the literature on how industrial clusters deal with digital transformation. The review takes a particular interest in industrial clusters, information and communication technologies, Industry 4.0 and policy tools for digital agglomeration.

The research develops the vision of the DIC as a new policy tool, building its foundations on both industrial clusters and digital economies; furthermore, the DIC was compared with other policy tools based on digital agglomeration to understand the similarities, differences and advantages of the former. Finally, this paper discussed where the DIC could find its way toward implementation and what externalities could be expected from doing so.

This research could be useful for policymakers and cluster organizations looking to deploy policy tools that take advantage of industrial clusters and digital transformation. Besides, the theoretical foundations presented could lead researchers to empirical identification of early incarnations of the DIC.

This paper develops theoretical principles for a new policy tool that connects industrial clusters, digital agglomeration and Industry 4.0 for the first time.

This study aims to focus on assessing the psychometric properties necessary to validate the internal structure of the TOURQUAL scale.

A quantitative research study was conducted in collaboration with the Brazilian Network of Tourism Observatories, comprising 927 respondents surveyed between October 2021 and May 2022. The data analysis involved the application of descriptive statistics and exploratory factor analysis, in alignment with the principles outlined in the Standards for Educational and Psychological Testing 2014 to validate the scale.

The findings of this study validate the TOURQUAL scale as a robust tool for assessing the perceived quality of tourist services, with results demonstrating one-dimensionality and replicability.

To the best of the authors’ knowledge, this study is the first to assess the psychometric properties for validating the internal structure of the TOURQUAL scale.

This paper proposes selecting a construction project portfolio in the context of a public institution, which makes it possible to assess quantitative and qualitative criteria, thereby meeting the needs of the institution and the existing constraints.

The research design follows a framework using technique for order preference by similarity to ideal solution (TOPSIS) associated with integer linear programming.

The method involves a flow of assessments allowing criteria and weights to be elicited where outcomes are based on the experts' intra-criteria assessment of alternatives and decision-makers' inter-criteria assessment. This is of utmost interest to public organizations, where selections must result in benefits and lower costs, integrating the experts' technical and management perspectives.

Public institutions are characterized by having limited financial and personnel resources for project development despite having a high demand for requests not associated with profits, making it essential to have a framework that enables using multiple criteria to better evaluate the benefits related to these decisions.

The main contributions of this article are: (1) the proposition of a framework for selecting construction project portfolios considering the organization's strategic needs; (2) identifying quantitative and qualitative assessment criteria for project selection; (3) integrating TOPSIS with an optimization process for selecting the construction project portfolios and (4) providing a structured decision process for selecting the portfolio that best represents the interests of the institution within its limited resources and personnel.

This study aims to investigate the influence of economic policy uncertainty (EPU) and geopolitical risk (GPR) on the relationship between internal cash flow and external financing in an emerging market, Saudi Arabia. It also examines the role of asset tangibility and financial crisis in establishing this relationship.

The sample was taken from non-financial sector companies listed on the Saudi Stock Exchange between 2002 and 2019. The data were analyzed using panel data regression analysis, including ordinary least squares and fixed effects model. The author addresses potential endogeneity through the generalized method of moments.

This study found that both EPU and GPR reduce the sensitivity of external financing to internal cash flow. This implies that firms depend more on internally generated funds during periods of increased EPU and GPR. Besides, this study found that the influence of EPU and GPR on the sensitivity of external financing to internal cash flow is more (less) negative for more tangible firms (during the financial crisis period). This result implies that Saudi firms boasting a higher level of tangibility are more flexible when it comes to seeking external financing. However, the presence of uncertainty during the crisis period makes the external financing costly, and therefore, firms will be less likely to raise funds from external sources.

This study has important implications for managers, policymakers and regulators. First, the paper findings provide insights for corporate decision-makers in helping them to focus on internal funds to finance their investment during uncertain times. Second, the findings help managers to understand the role of asset tangibility in raising external funding when firms face financial constraints due to uncertainty. Third, this study also helps corporates to focus on internal funds to finance their investment during the crisis period because EPU and GPR increase the cost of external finance. Finally, the results provide guidelines for policymakers and regulators to make appropriate policy measures to increase the easy availability of external finance during periods of increased EPU and GPR.

This paper is the first to shed light on the impact of internal funds on external financing while paying close attention to the role of EPU and GPR.

The purpose of this paper is to develop a conceptual framework that examines the impacts of changing seasons on tourism.

The paper presents a conceptual process model of the impact of seasons on all aspects of in-destination tourist behaviour. The model is developed from the literature and is then tested using Cairns, Australia as a case study.

Seasons influence the actual and perceived range of products/experiences available, which dictate the pull features of a destination, that in turn, influence who comes and why they come. Combined the activity sets and visitor profile define in-destination behaviour and, ultimately, satisfaction.

The study fills a needed research gap in two ways. Firstly, it explains conceptually and then tests empirically how changes in seasons affect the delivery of tourism products and experiences. Secondly, it adds significantly to our understanding of the factors that influence in-destination behaviour.

Managerial implications for destination management organisations are identified.

This paper presents a new conceptual process model for a previously unexamined issue.

本文提出了一个季节影响目的地游客行为的过程的理论模型。该模型基于文献开发而成, 然后以澳大利亚凯恩斯作为案例进行测试。

本文的目的是开发一个研究季节变化影响旅游的理论框架。

研究发现季节会影响实际和感知的产品或体验的范围, 从而决定一个目的地的吸引力特征。他们反过来可以影响谁来旅游以及他们来旅游的原因。 结合活动和旅游者画像来定义其目的地行为。

这项研究从两个方面填补了理论空白。 首先, 它从概念上解释, 然后实证检验了季节的变化如何影响旅游产品和体验的供应。 其次, 它极大地增强了我们对影响目的地行为的因素的理解。

本文指出了对目的地管理的实践意义。

本文针对先前未经考察的问题提出了一种新的理论过程模型。

El artículo presenta un modelo de proceso conceptual del impacto de las estaciones en todos los aspectos del comportamiento en en destino turístico. El modelo se desarrolla a partir de la literatura y luego se pone a prueba usando Cairns, Australia como estudio de caso.

El propósito de este artículo es desarrollar un marco conceptual que examine los impactos de los cambios de estación en el turismo.

Las estaciones influyen en la gama, real y percibida, de productos/experiencias disponibles que condicionan las características de atracción de un destino. Las estaciones, a su vez, influyen en quién viene y por qué viene. Los conjuntos de actividades combinadas y el perfil del visitante definen el comportamiento en el destino.

El estudio llena un vacío de investigación necesario de dos maneras. Primero, explica conceptualmente y luego demuestra empíricamente cómo los cambios en las estaciones afectan la oferta de productos y experiencias turísticas. En segundo lugar, contribuye significativamente a la comprensión de los factores que influyen en el comportamiento en el destino.

Se identifican las implicaciones de gestión para las organizaciones de gestión de destinos.

Este artículo presenta un nuevo modelo de proceso conceptual para un tema no examinado previamente.

This study analyzes whether industry relatedness between a corporate borrower and its group peers significantly affects that firm's borrowing cost.

A regression analysis is run on bank-loan data of a sample of Indonesian companies for 2010–2020. The main variables of interest are the natural logarithms of the borrowing firm's number of affiliates classified within either similar 2- or 4-digit GICS industries, and the Caves weighted index of these firms' related diversification. This index measures how firms in a group are diversified in relation to the borrower. The dependent variable is the all-in credit spread, stated in basis points, over the LIBOR or similar benchmark, as of the loan issuance date.

Findings support the industry-relatedness hypothesis and contradict the risk-reduction hypothesis and show that banks charge lower loan spreads on a borrowing firm that either operates within a similar industry as its affiliate or diversifies into related sectors or industries. Consistent with the co-insurance-effect hypothesis, the results also underline the importance of the parent and first-layer firms as supporting instead of the tunneling vehicles within business groups. These conclusions hold even after segregating the sample and using the loan maturity as the dependent variable.

This study uses a unique diversification measurement based on the borrowing firm's sector or industry, relative to other group members, and offers new insights on business group diversification and bank loan costs.

Small and medium-sized enterprises (SMEs) are currently showing an increasingly open innovation (OI) approach. Public policies supporting the adoption of OI by SMEs are becoming a priority for policymakers. Therefore, the aim of this article is to contribute to the literature by mapping scholars' policy recommendations for implementing OI among SMEs.

The authors conducted a systematic review of the literature (SRL) on the topic to achieve this purpose. A total of 99 academic articles were selected from the Web of Science and Scopus databases to suggest the main scholars' policy recommendations to implement OI among SMEs.

Results indicated that scholars' policy recommendations for OI adoption in SMEs can be organized into: research and development (R&D), networking, collaboration, knowledge and intellectual property rights (IPR), ecosystem, managerial capabilities, funding and incentives and sustainability policies.

Only relevant articles about this topic have been included due to the reliance on the interpretations of the authors. The analysis of the literature revealed that the authors did not always distinguish policies dedicated to SMEs and those dedicated to large companies. Moreover, policies are not matched according to each OI dimensions (e.g. inbound, outbound and coupled OI).

The article uses a systematic literature review method that combines qualitative and quantitative analyses. This method contributes to theoretical development of OI policies dedicated, in particular to SMEs. This paper also provides policymakers and researchers with insights on the scope of OI policies that could support economic growth.

Destinations to be able to compete with each other need to equip themselves with as many competitive advantages as possible. Tourists' loyalty to a destination is considered as a prominent competitive tool for destinations. Tourists' loyalty manifests itself in recommendation of the destination to others, repeat visit of the destination and willingness to revisit the destination. Although a plethora of studies have tried to define models to show the relation between loyalty and the antecedent factors leading up to it, few of them have tried to integrate these models with mathematical approaches for better understanding of loyalty behavior. The purpose of this paper is to integrate a tourist destination model with Bayesian Network in order to predict the behaviour of destination loyalty and its antecedent factors.

This paper has developed a probability model by the integration of a destination loyalty model with a Bayesian network (BN) which enables to predict and analyze the behavior of loyalty and its influential factors. To demonstrate the application of this framework, Tehran, the capital of Iran, was chosen as a destination case study.

The outcome of this research will assist in identifying the weak key points in the tourist destination area for giving insights to the marketers, businesses and policy makers for making better decisions related to destination loyalty. In the analysis process, the most influential factors were recognized as the travel environment image, natural/historical attractions and, with a lower degree, infrastructure image which help the decision maker to detect and reinforce the weak factors and put more effort in focusing on improving the necessary parts rather than the irrelevant parts.

The research identified all critical factors that have the most influence on destination loyalty while driving the associate uncertainty which is significant for the tourism industry. This resulted in better decision-making which is used to identify the impact of tourism destination loyalty.