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Green consumption is fundamental to sustainable development, as it involves adopting practices and technologies that reduce the environmental impact of human activities. This study aims to analyze the influence of consumers’ green orientation on their environmental concerns and green purchase decisions. Furthermore, the study investigates the mediating role of consumers’ environmental concerns in the relationship between pro-sustainable orientation and green purchase decisions.

This study uses a quantitative methodology, applying the partial least squares method to a sample of 927 Portuguese consumers of green products. The sample was collected through an online survey.

Perceived benefits and perceived quality of products play a positive and significant role in influencing green behavior, especially when consumers are endowed with greater environmental concerns. In addition, consumers’ awareness of the prices of green products and their expectations regarding the future benefits of sustainable consumption positively impact green consumption behavior, further intensifying their environmental concerns.

According to the present findings, companies should adopt a holistic and integrated approach to promote green consumption. This means creating premium eco-friendly products, communicating their benefits, addressing the cost factor, emphasizing the future impact of eco-friendly options and raising consumers’ environmental awareness.

It is critical that environmental education is a priority in schools and that there are political incentives for green behaviors. In addition, media campaigns can be an important tool to raise awareness in society.

The results of this study provide important insights for companies on consumer engagement in the circular economy. Deepening knowledge of the antecedents of consumers’ environmental concerns contributes to a deeper understanding of green purchasing decision behavior, allowing companies to support new business strategies.

Optimal application and commitment toward financial management practices enhance organization performance. This study aims to assess the influence of financial management practices on organizational performance of small- and medium-scale enterprises.

Data were collected from 45 small-sized and 72 medium-sized firms. Data supported the hypothesized relationships. Construct reliability and validity were established through confirmatory factor analysis. The conceptual model and hypotheses were evaluated by using structural equation modeling.

The results indicate that working capital significantly influenced organizational performance. Capital budget management significantly influenced organizational performance. A non-significant influence of asset management on organizational performance was observed.

The generalizability of the findings will be constrained due to the research’s SMEs focus and cross-sectional data.

The study’s findings will serve as valuable pointers for stakeholders and decision-makers of SMEs in the development of well-articulated and proactive financial management systems to ensure competitiveness, sustainability, viability and financial competences.

The study adds to the corpus of literature by evidencing empirically that financial management practices significantly influenced SMEs’ performance.

This paper aims to analyze the link between universities and business incubators (BIs) and to determine how students, scientific researchers and entrepreneurs can benefit from this linkage. It creates an environment in which everyone can help the other to put their new ideas, special skills and abilities into new businesses. In other words, the traditional universities’ role has changed and entrepreneurial universities are now needed to redirect new knowledge for economic development through BIs.

This paper adopts an analytical descriptive methodology approach to describe the basic features of the data by using the descriptive research design. This research is based on examining a model provided by the author concerning boosting the entrepreneurial aspects and outcomes through university business incubators (UBIs) based on wide theoretical and empirical case studies. Also, the functional structural approach is used to investigate the relationship between two variables as UBIs are considered a new unit that has functions and structures to create an added value to universities and the society as a whole.

The educational system should create a favorable environment that enables young people to develop their mindset from employees to employers, and to prepare them to improve skills and knowledge to create jobs. UBI is the recent aspect of the BI evolution where the research outcomes are linked with the industry and development. This relationship between these entities will provide success to its stakeholders.

Many incubators around the world are supported by universities. Others are making initiatives to link up with universities and higher education institutions to get the revenues and returns from its academic nature. Lately, university incubators became a type of incubator evolution and more supportive for entrepreneurs than other types of incubators.

The contribution of this study is to explain how UBIs succeeded to tie the results of scientific research with economy and development through entrepreneurial activities to accelerate and realize entrepreneurship strategies.

This study aims to estimate the impact of refugee inflows on host countries’ entrepreneurial rates. The refugee crisis led to an increased scientific and public policy interest in the impact of refugee inflows on host countries. One important perspective of such an impact, which is still underexplored, is the impact of refugee inflows on host countries entrepreneurial rates. Given the high number of refugees that flow to some countries, it would be valuable to assess the extent to which such countries are likely to reap the benefits from increasing refugee inflows in terms of (native and non-native) entrepreneurial talent enhancement.

Resorting to dynamic (two-step system generalized method of moments) panel data estimations, based on 186 countries over the period between 2000 and 2019, this study estimates the impact of refugee inflows on host countries’ entrepreneurial rates, measured by the total early-stage entrepreneurial activity (TEA) rate and the self-employment rate.

In general, higher refugee inflows are associated with lower host countries’ TEA rates. However, refugee inflows significantly foster self-employment rates of “medium-high” and “high” income host countries and host countries located in Africa. These results suggest that refugee inflows tend to enhance “necessity” related new ventures and/ or new ventures (from native and non-native population) operating in low value-added, low profit sectors.

This study constitutes a novel empirical contribution by providing a macroeconomic, quantitative assessment of the impact of refugee from distinct nationalities on a diverse set of host countries' entrepreneurship rates in the past two decades resorting to dynamic panel data models, which enable to address the heterogeneity of the countries and deal with the endogeneity of the variables of the model.

Transaction cost economics sees a broad spectrum of governance structures spanned by two types of economic adaptation: autonomous and cooperative. Stakeholder theorists have drawn much inspiration from transaction cost economics but have not paid explicit attention to the centrality of the idea of adaptation in this literature. This study aims to address this gap.

The authors develop a novel conceptual framework applying the distinction between the two types of economic adaptation to stakeholder theory.

The authors argue that the idea of cooperative adaptation is particularly useful for describing the firm’s collaboration with primary stakeholders in the joint value creation process. In contrast, autonomous adaptation is more relevant for firms interacting with secondary stakeholders who are not directly engaged in joint value creation and may not have formal contractual relationships with the firm. Accordingly, cooperative adaptation can be seen as vital for resolving team production problems affecting joint value creation, whereas autonomous adaptation addresses how the firm maintains legitimacy within the larger stakeholder environment.

Similar to its significance for transaction cost economics, the distinction between the two types of adaptation equips stakeholder theory with a new systematic understanding of a potentially broad spectrum of firm–stakeholder collaboration forms.

Traditional payment systems based on cash and bank cards are being replaced by new innovative formats. This research analyzes the success factors in the adoption by customers of Bizum, a peer-to-peer (P2P) mobile payment system widely used in Spain. This study proposes a theoretical framework based on the Stimulus–Organism–Response (S-O-R) model and includes the analysis of the moderating effect of perceived risk and the mediating effect of perceived trust.

To achieve the proposed objectives, an online questionnaire was administered to 701 Spanish smartphone users, potential users of the proposed P2P payment systems.

The results show that perceived usefulness is the most important predictor of intention to use. Additionally, a medium predictive relevance performance of the proposed model is found.

This research contributes to a more holistic understanding of the adoption of P2P payment systems and provides new business opportunities that companies can exploit through the use of this technology.

以現金和銀行卡為基礎的傳統支付系統、正被嶄新而又富創意的模式取代。本研究擬分析驅使消費者使用Bizum的成功因素 (Bizum 是一個在西班牙得到廣泛使用的P2P移動支付系統) 。本研究以刺激-有機體-反應模型為基礎, 建議了一個概念框架;研究亦擬分析感知風險的調節作用, 以及感知信任的中介效應。

為達研究目標, 研究人員處理了701名西班牙智慧型手機使用者回答的網上問卷, 這些使用者是本研究提出的P2P支付系統的潛在用戶。

研究結果顯示、感知有用性是消費者會否使用P2P支付系統最重要的預測因素。研究結果亦顯示、本研究建議的概念框架的預測能力水平屬中等。

本研究使我們對驅使消費者使用P2P支付系統的因素更全面地了解;研究也使企業可透過使用這技術, 為自己創造新的商機。

This research paper aims to handle the effects of economic growth, corruption, energy consumption as well as trade openness on CO2 emissions for a sample of West African countries during the period 1980 and 2018.

The current work uses the pooled mean group (PMG)-autoregressive distributed lag (ARDL) panel model to estimate the dynamics among the different variables used in the short and long terms.

The findings demonstrate that all variables have long-term effects. These results suggest that gross domestic product (GDP) per capita exhibits a positive and prominent effect on CO2 emissions. Corruption displays a negative and outstanding effect on long-term CO2 emissions. In contrast, energy consumption in West African countries and trade openness create environmental degradation. Contrarily to long-term results, short-term results demonstrate that economic growth, corruption and trade openness do not influence the environmental quality.

Empirical findings provide useful information to explore deeper and better the link between the used variables. They stand for a theoretical basis as well as an enlightening guideline for policymakers to set strategies founded on the analyzed links.

Radical changes in consumer habits induced by the coronavirus disease (COVID-19) pandemic suggest that the usual demand forecasting techniques based on historical series are questionable. This is particularly true for hospitality demand, which has been dramatically affected by the pandemic. Accordingly, we investigate the suitability of tourists’ activity on Twitter as a predictor of hospitality demand in the Way of Saint James – an important pilgrimage tourism destination.

This study compares the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) time-series model with that of the SARIMA with an exogenous variables (SARIMAX) model to forecast hotel tourism demand. For this, 110,456 tweets posted on Twitter between January 2018 and September 2022 are used as exogenous variables.

The results confirm that the predictions of traditional time-series models for tourist demand can be significantly improved by including tourist activity on Twitter. Twitter data could be an effective tool for improving the forecasting accuracy of tourism demand in real-time, which has relevant implications for tourism management. This study also provides a better understanding of tourists’ digital footprints in pilgrimage tourism.

This study contributes to the scarce literature on the digitalisation of pilgrimage tourism and forecasting hotel demand using a new methodological framework based on Twitter user-generated content. This can enable hospitality industry practitioners to convert social media data into relevant information for hospitality management.

2019冠狀病毒病引致消費者習慣有根本的改變; 這些改變顯示，根據歷史序列而運作的慣常需求預測技巧未必是正確的。這不確性尤以受到大流行極大影響的酒店服務需求為甚。因此，我們擬探討、若把在推特網站上的旅遊活動視為聖雅各之路 (一個重要的朝聖旅遊聖地) 酒店服務需求的預測器，這會否是合適的呢?

本研究比較 SARIMA 時間序列模型與附有外生變數 (SARIMAX)模型兩者在預測旅遊及酒店服務需求方面的表現。為此，研究人員收集在推特網站上發佈的資訊，作為外生變數進行研究。這個樣本涵蓋於2018年1月至2022年9月期間110,456個發佈資訊。

研究結果確認了傳統的時間序列模型，若涵蓋推特網站上的旅遊活動，則其對旅遊需求方面的預測會得到顯著的改善。推特網站的數據，就改善預測實時旅遊需求的準確度，或許可成為有效的工具; 而這發現對旅遊管理會有一定的意義。本研究亦讓我們進一步瞭解朝聖旅遊方面旅客的數碼足跡。

現存文獻甚少探討朝聖旅遊的數字化，而本研究不但在這方面充實了有關的文獻，還使用了一個根據推特網站上使用者原創內容嶄新的方法框架，進行分析和探討。這會幫助酒店從業人員把社交媒體數據轉變為可供酒店管理之用的合宜資訊。

In this study the authors aim to comprehensively investigate the determinants of voting behavior in Turkey, with a specific focus on the dynamics of the center-periphery debate. Mainly, the authors focus on regional voting patterns during the period that is dominated by the Justice and Development Party (JDP/AKP) in the elections. The authors apply the random effects generalized least squares (GLS) methodology, and analyze electoral data covering four pivotal parliamentary elections (2007, 2011, 2015 and 2018) across all 81 provinces (NUTS III regions). The authors individually examine voting dynamics of the four major parties in parliament: the JDP/AKP, the Republican People's Party (RPP/CHP), the Nationalist Movement Party (NMP/MHP) and the Peoples' Democratic Party (PDP/HDP). The authors contribute to a comprehensive understanding of how socioeconomic cleavages, economic performance, party alignment and social dynamics shape voter preferences in the Turkish context, thereby addressing gaps in the existing literature.

This research employs an ecological study of Turkish NUTS III sub-regions, covering national elections from 2007 to 2018. The authors utilize the random effects GLS method to account for heteroscedasticity and time effects. The inclusion of the June and November 2015 elections enables a comprehensive analysis of the evolving dynamics in Turkish voting behavior. The results remain robust when applying pooled OLS and fixed effect OLS techniques for control.

The study's findings reveal that economic performance, specifically economic growth, plays a pivotal role in the sustained dominance of the JDP/AKP party. Voters closely associate JDP preference with economic growth, resulting in higher voting shares during periods of economic prosperity. Along with economic growth; share of agriculture in regions' GDP, female illiteracy rate, old population rate, net domestic migration, terrorism and party alignment are also influential factors in the Turkish case. Furthermore, differences among sociocultural groups, and East–West dichotomy seem to be important factors that reveal the impact of social cleavages to understand electoral choice in Turkey.

This study contributes to the existing literature by offering a comprehensive multidimensional analysis of electoral behavior in Turkey, focusing on the JDP/AKP dominance period. The main contribution of this study is its multidimensional perspective on the power bases of all main parties, considering key voter choice theories (cleavages, party alignment and retrospective economic performance voting) that have not been systematically analyzed in prior research. The main research question of this study is to examine which factors affect voting behavior in Turkey and how the dynamics of center-periphery or eastern-western region voting behavior under the JDP hegemony can be explained. The contribution of this study consists not only in its empirical testing of panel data approaches but also in its comprehensive analysis of four major political parties. Building upon existing studies in the literature, this research seeks to extend the understanding of voting dynamics for the four main parties in the parliament — JDP/AKP, RPP/CHP, NMP/MHP and PPDP/HDP — by delving into their dynamics individually, thereby expanding the scope of previous studies. This study aims to make a contribution by not only empirically testing panel data approaches but also conducting a comprehensive analysis of four major political parties. Furthermore, the separate inclusion of the 2015 elections and utilization of a panel data approach enrich the analysis by capturing the evolving dynamics of Turkish voting behavior. The study underscores the significance of socioeconomic factors, economic performance and social cleavages for voters' choices within the context of a dominant party rule.

The key aim of this study is to highlight current financial technology (FinTech) trends by conducting a bibliometric review of literature derived from the Scopus database.

A bibliometric analysis was conducted on articles gathered from the Scopus database. Microsoft Excel was used to perform the frequency analysis, VOSviewer for visualising the data, and Harzing’s Publish or Perish for the metrics citation.

According to this investigation, research into FinTech has been consistently increasing since 2008. The results indicate that the most active publisher of FinTech literature is Bina Nusantara University in Indonesia. In terms of country of publication, China is identified as the most active. The most cited author is Buckley, R.P., with Rabbani, M.R., having the most publications. It was also identified that FinTech researches come under three primary domains namely business management, computer science and economics.

The primary limitation of this current study is that it only relied on one data source, i.e. Scopus. Implications wise, researchers and practitioners can gain a deeper understanding of FinTech from this study, which also describes the trend in related publications on the concept. Future studies could significantly benefit from the findings of the present paper.

The outcomes of this study can assist researchers in better comprehending and summarising the key drivers of FinTech. In addition, the findings can help new researchers identify the starting point for their research on FinTech.

As far as the authors are aware, this is the first study that reviews FinTech publications derived from Scopus from 2008 to 2022. Hence, it is a pioneering study into FinTech bibliometric analysis, providing an understanding of the structural knowledge by reviewing the timeline of academic progression in FinTech.