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The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.

This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

The purpose of this study is to explore the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports.

Based on the theoretical analysis of the mechanism of the digital economy’s influence on the binary margin of agricultural exports, this study empirically examines the effect and mechanism of the digital economy’s influence on the binary margin of agricultural exports based on China’s customs export data from 2011 to 2016.

The relevant findings are threefold. (1) The digital economy significantly improves the binary margin of agricultural exports, and its effect on the intensive margin is stronger than that on the expansive margin. After the expansive margin is subdivided, the effects on the three sub-variables of the expansive margin are in the following order: old products exported to new markets > new products exported to old markets > new products exported to new markets. (2) The heterogeneity analysis reveals that the digital economy has a stronger role in promoting the binary margin of exports for enterprises in the eastern region, high-income countries as the destination of exports and state-owned enterprises. (3) Mechanism analysis shows that the digital economy promotes the binary margin of agricultural exports by reducing trade costs and intensifying market competition.

First, in terms of research perspective, although there are some studies on the impact of the digital economy on export trade in existing literature, the research objects mainly focus on manufacturing enterprises. In fact, agricultural trade is susceptible to natural conditions and seasonal factors, and countries may impose more SPS measures and TBT measures on agricultural trade due to risk considerations. The relationship between the digital economy and agricultural trade also has its own characteristics, but there are few research studies in this area. At present, only Liu and Gao (2022), based on the data of total imports and exports of different agricultural products from 2004 to 2018, have established a vector auto-regressive model to empirically analyse the heterogeneous dynamic impact of the digital economy on the trade volume of agricultural products. In addition, Ma and Guo (2023) conducted an empirical test on the total effect, regional heterogeneity and threshold effect of the digital economy on agricultural export trade based on China’s provincial panel data from 2011 to 2020. Therefore, under the new circumstances of continuous integration of digital technology and agriculture, this study interprets the impact effect and mechanism of the digital economy on the binary margin of agricultural exports from the perspective of the digital economy, providing new research perspectives and approaches for promoting the growth of agricultural exports. Second, in terms of theoretical analysis, the above studies have not been fully analysed in terms of the specific mechanism of the impact of the digital economy on agricultural exports. Based on the positive and negative characteristics of agricultural trade, this study introduces two kinds of roles into the theoretical analysis framework to comprehensively determine the trade impact effect of the digital economy. Third, in terms of research design, this study empirically examines the impact of the digital economy on the binary margin of agricultural products, passing a series of robustness tests and investigating the mediating roles of trade cost and market competition effects, producing an empirical basis for China to leverage the digital economy to promote the binary margin of agricultural exports.

This paper aims to analyze practices, processes and outcomes related to construction supply chain management (CSCM) in Brazil to identify opportunities and direct actions and strategies to improve the Brazilian sector through blockchain technology (BT).

The study collected empirical data through semi-structured interviews with consumers and distributors to identify how the CSCM functions today. The interviews were structured and analyzed around the following topics: processes, digitalization, quality and weakness of the activities performed. The opportunities for using BT in CSCM were identified by crossing these results with evidence in the bibliography.

The study identified deficiencies, gaps and good practices applied to information management in the sector. Also, it analyzed the features, drivers and barriers of BT from a practical perspective. The findings suggested that BT is feasible and promising, reducing costs and enhancing process transparency. The need to overcome cultural and economic barriers is a challenging task.

This study brings a new perspective on using BT in CSCM, relating it to the demands and particularities of the construction sector in Brazil. The study identifies a limited panorama of chronic CSCM concerns, given BT’s infinite opportunities. And it motivates a gradual transition toward installing a new technological culture based on BT that focuses on priority care for the sector’s chronic deficiencies. The results can guide practical actions for the successful insertion of BT in the CSCM, laying the foundations for significant future research.

Small-to-medium-sized enterprises (SMEs) in e-commerce often invest in information technology (IT) to stay competitive. However, whether and how IT capability (ITC) translates into financial performance requires further research. This paper examines the role of ITC in enabling value proposition innovation (VPI) as an important mechanism that improves financial performance for Chinese e-commerce SMEs during the COVID-19 pandemic. We argue that ITC is critical for enabling innovation because it elevates SMEs’ understanding of changing customer needs, especially when SMEs operate on multiple e-commerce platforms (multihome).

We used partial least squares structural equation modeling (PLS-SEM) and tested the hypotheses that ITC mediated by VPI and moderated by multihoming increases the financial performance of e-commerce SMEs through a survey among 206 Chinese SMEs operating on Taobao.

We find that not only higher levels of ITC lead to better financial performance, but also that the effect is fully mediated by VPI. Moreover, the effect of ITC on innovation is enhanced when vendors operate on multiple platforms.

The study identifies VPI as an important mechanism through which SMEs can leverage their ITC to adapt, innovate and thrive in competition. Our work suggests that using technology to develop innovative ideas and identify opportunities (which are reflected in VPI) is key to success and that doing so is more likely when vendors multihome. Thus, this study contributes to the innovation literature by explicating a concrete link between ITC, multihoming, VPI and increased financial performance. Different e-commerce stakeholders, including SME owners, IT and service providers and e-commerce platforms, can benefit from the findings of this work.

This paper reviews recent research on the expected economic effects of developing artificial intelligence (AI) through a survey of the latest publications, in particular papers and reports issued by academics, consulting companies and think tanks.

Our paper represents a point of view on AI and its impact on the global economy. It represents a descriptive analysis of the AI phenomenon.

AI represents a driver of productivity and economic growth. It can increase efficiency and significantly improve the decision-making process by analyzing large amounts of data, yet at the same time it creates equally serious risks of job market polarization, rising inequality, structural unemployment and the emergence of new undesirable industrial structures.

This paper presents itself as a building block for further research by introducing the two main factors in the production function (Cobb-Douglas): labor and capital. Indeed, Zeira (1998) and Aghion, Jones and Jones (2017) suggested that AI can stimulate growth by replacing labor, which is a limited resource, with capital, an unlimited resource, both for the production of goods, services and ideas.

Our study contributes to the previous literature and presents a descriptive analysis of the impact of AI on technological development, economic growth and employment.

In the context of the Covid-19 pandemic and the trend in industrial development 4.0, the problem is how to conduct transactions of goods and services in the market using cashless payment in Vietnam, as in developed countries. This study aims to investigate, analyze and evaluate the factors affecting cashless payment behavior in Ho Chi Minh City, Vietnam.

The QR codes are used for payments because many factors affect the behavior of cashless payments made using electronic payment tools, including QR code tools. To achieve this goal, this study applied behavioral theory and the importance-performance analysis (IPA) model to measure service quality based on the difference between customer opinions on the importance and performance level of service providers’ targets. Survey results were obtained from 111 people living in HCMC, Vietnam, including 47 men and 64 women, which was a survey for 15 criteria.

According to the IPA results of the first quadrant, managers should focus on allocating their resources toward improving their performance across five key criteria. These criteria are crucial for meeting customers’ expectations and include factors such as product quality, responsiveness to customer queries or complaints, delivery times, pricing and customer service. In addition, the second quadrant of the IPA highlights another set of five criteria that perform well and are essential to the success of the business. These criteria could consist of customer loyalty, employee satisfaction, profitability, market share and innovation

These results provide a basis for solutions and recommendations for managers to refer to and apply consistent practices. Therefore, this study examines the cashless payment in Vietnam. Empirical results offer solutions to financial technology policy, marketing policy, cashless payment services and technology, which can help managers provide online payments using QR codes and contribute to monetary policy solutions.

To extend research into sport consumer behaviors related to online sports betting, this study is designed to identify and examine the relationship between online sports betting motivations and online sports betting intentions. By applying a push-pull framework from online sport consumption and gambling studies, nine motivations to engage in online sports betting were identified. These motivations were hypothesized to motivate online sports betting intentions.

A quota sampling technique based on the sports bettor demographics available in the American Gaming Association (AGA, 2019) and the Pew Research Center (2022) obtained a total of 550 completed surveys that met the inclusion and exclusion criteria. For data analyses, confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to examine the measurement model and the hypothesized model, respectively.

The results revealed that four motivations (i.e. monetary gain, excitement, convenience and negative technology-readiness) were related to online sports betting intention, while five motivations (i.e. sport fandom, positive technology-readiness, impulsivity, socialization and promotion) were not.

The results provide foundational theoretical knowledge of what motivates sports fans to participate in online sports betting. Furthermore, the findings assist practitioners in their allocation of resources by enhancing their understanding of online sports betting motivations.

Academic literature calls for research on the impact of psychological states derived from mental illness on detrimental consumer behaviour. The purpose of this study is to assess the impact of anxiety on the consumer’s buying processes (compulsive and impulsive) and emotional regulation.

To carry out the statistical analysis, the data were obtained through an online survey (n = 726) of supermarket consumers. The treatment of the data was using partial least squares structural equation modelling (PLS-SEM).

The results obtained show that anxiety influences the generation of harmful behaviour, as it has a positive impact on compulsive and impulsive buying. In addition, compulsive and impulsive buying generate higher levels of consumers’ emotional regulation.

This study contributes to the management of anxiety as a priority element to reduce harmful behaviour. Therefore, it provides useful information for marketing managers and professionals in psychological and healthy consumer processes.

學術文獻不斷呼籲研究人員和學者去探討來自精神病的心理狀態如何產生有害的消費者行為。本研究擬評定焦慮對消費者購買流程 (強迫性購物和衝動購物) 和情緒調節所產生的影響。

為能進行統計分析,研究人員透過超級市場消費者的在線調查 (n = 726) 取得數據,繼而以結構方程 (PLS-SEM) 處理數據。

研究結果顯示,焦慮會導致有害行為的產生,這是因為焦慮對強迫性購物和衝動購物均產生積極的影響; 而且,強迫性購物和衝動購物會產生較高水平的消費者情緒調節。

本研究的貢獻在於把焦慮視為減少有害行為的優先元素而予以管理; 因此,本研究為市場經理以及於心理上的和健康的消費者進程的專業人員提供了有用的資料。

Considering food waste as a global problem resulting from the wastage of valuable resources that could fulfil the requirements of malnourished people, the current research focusses on understanding consumerism’s impact on this phenomenon. Additionally, the circular economy (CE) approach can be critical in reducing food waste and promoting sustainability.

A systematic literature review was conducted using bibliometrics and network analysis. The study reviewed 326 articles within 10 years, from 2013 to 2023.

The findings reveal four prominent factors – behavioural, environmental, socioeconomic and technological – in managing food waste (FW). Reducing FW at a holistic level can benefit individuals and the environment in several ways.

Consumers are encouraged to be more responsible for their food consumption by reducing food waste, as it affects societies and businesses both economically and environmentally. This can help promote a responsible consumption culture that values quality over quantity and encourages people to make more informed choices about what they eat and how they dispose of it post-consumption. All stakeholders, including firms, the government and consumers, must examine the motives behind inculcating pro-environmental behaviour.

Addressing consumerism and the ability to decrease FW behaviour are complex issues that require a multidimensional approach. This study seeks to fill the gap in understanding consumerism and the capacity to reduce FW using the CE approach and understand the research gaps and future research trends.