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This study aims to explore the relationship between elderly users' trust in public digital cultural services (PDCS) and their intention to use PDCS, and reveal the factors affecting their intentions from the perspective of trust to make recommendations that will increase their intention to use PDCS.

Combined with the trust building model and social exchange theory, this study constructed a conceptual model of elderly users' intention to use PDCS. Data collected from Chinese elderly users who have reached the age of 60 through questionnaire surveys were tested using the structural equation model with partial least squares. Finally, the authors proposed a model of elderly users' intention to use PDCS.

This study finds that elderly users' trust positively affects their intention to use PDCS from two aspects: service features and user features of PDCS. Concerning the service features, system quality directly affects elderly users' trust in PDCS most significantly, followed by information quality and service reputation. Concerning the user features, perceived value has a higher impact on elderly users' trust than that of service features, and information literacy and information quality directly affect perceived value.

This study adds new knowledge to the users' behavior of PDCS and enriches the prior description of PDCS. The recommendations made in this study provide a series of strategies for practitioners and researchers to improve the elderly users' intention to use PDCS and bridge the silver digital divide, which offers new ideas for improving the efficiency of PDCS.

In recent years, the use of mobile devices for academic persistence has grown to be an indispensable element of students’ learning, highlighting the broad acceptance and adaptability of mobile technology in learning environments. The current study examines how college students in rural areas use mobile devices and how self-efficacious they are when seeking online information. Additionally, the study investigated the connection between mobile devices usage (MDU), mobile devices self-efficacy (MDSE) and online information seeking behavior (OISB) on the basis of demographic differences.

A quantitative research design was used by deploying a five-point Likert scale for measurement, Statistical Package for Social Sciences (SPSS) v.26 was used for data analysis. A variety of statistical methodologies, including t-tests, ANOVA and correlation coefficients, were conducted to inspect and assess MDU, MDSE and OISB across gender and age groups. Data from 331 students at the public sector college in a rural region was gathered using a questionnaire. A total of 315 legitimate replies were received.

The study's conclusions showed that the respondents used their mobile devices for educational purposes less frequently. Nonetheless, the respondents' degrees of MDSE and OISB appear to be high. Furthermore, a strong link was demonstrated among the MDU, MDSE and OISB. On the contrary, there was a negative correlation link between MDU and both MDSE & OISB, while a positive correlation between MDSE and OISB was found. The results also showed substantial variance in all research components based on age and gender, indicating that male and younger respondents performed more efficiently than female and adult respondents.

These results indicate that information literacy guidelines and a variety of educational initiatives should be put together by the government, educational policymakers, librarians and educators, with a focus on how to use mobile devices for learning and information seeking. This will make it possible for students to more efficiently find the information using their portable devices.

The study aims to examine the impact of cultural dependency stemming from exchange rate fluctuations (specifically the US dollar) on herding behavior in the housing market across 31 provinces of Iran from Q2 2011 to Q1 2022, using a spatial econometrics approach. After confirming the presence of spatial effects, the Dynamic Spatial Durbin Panel Model with Generalized Common Effects (SDM-DPD(GCE)) was selected from various spatial models for these provinces.

The study examines the impact of cultural dependency stemming from exchange rate fluctuations (specifically the US dollar) on herding behavior in the housing market across 31 provinces of Iran from Q2 2011 to Q1 2022, using a spatial econometrics approach. After confirming the presence of spatial effects, the Dynamic Spatial Durbin Panel Model with Generalized Common Effects (SDM-DPD(GCE)) was selected from various spatial models for these provinces.

The model estimation results indicate that fluctuations in the free market exchange rate of the dollar significantly and positively impact the housing market in both target and neighboring regions, fostering herding behavior characterized by cultural dependency within the specified timeframe. Additionally, the study found that variables such as the inflation rate, population density index and the logarithm of stock market trading volume have significant and positive impacts on the housing market. Conversely, the variable representing the logarithm of the distance from the provincial capital, Tehran, significantly and negatively impacts the housing market across Iranian provinces.

Given that housing is a fundamental need for households, the dramatic price increases in this sector (for instance, a more than 42-fold increase from 2011–2021) have significantly impacted the welfare of Iranian families. Currently, considering the average housing price in Tehran is around 50 million Tomans, and the average income of worker and employee groups is 8 million Tomans (as of 2021), the time required to purchase a 100-square-meter house, even with a 30% savings rate and stable housing prices, is approximately 180 years. Moreover, the share of housing and rent expenses in household budgets now constitutes about 70%. The speculative behavior in this market is so acute that, despite 25 million of Iran’s 87 million population being homeless or renting, over 2.5 million vacant homes (12% of the total housing stock) are not used. Therefore, various financial behaviors and decisions affect Iran’s housing market. Herd behavior is triggered by the signal of national currency devaluation (with currency exchange rates increasing more than 26-fold between 2011 and 2021) and transactions at higher prices in certain areas (particularly in northern Tehran) (Statistical Center of Iran, 2023). Given the origins of housing price surges, a price increase in one area quickly spreads to other regions, resulting in herd behavior in those areas (spillover effect). Consequently, housing market spikes in Iran tend to follow episodes of currency devaluation. Therefore, considering the presented discussions, one might question whether factors other than economic ones (such as herd behavior influenced by dependence culture) play a role in the rising housing prices. Or, if behavioral factors were indeed contributing to the increase in housing prices, what could be the cause of this herd movement? Has the exchange rate, particularly fluctuations in the free market dollar rate, triggered herd behavior in the housing market across Iran’s provinces? Or has the proximity and neighborhood effect been influential in the increase or decrease in housing prices in the market?

This study aims to construct alternative models to establish the dynamic relationship between exchange rates and housing affordability by estimating both the short- and long-run relationship between exchange rates and housing affordability for 18 OECD countries from 1975Q1 to 2022Q4. After that, this study demonstrates how this nexus behaves during high and low inflation regimes and turbulent times.

This study uses the panel autoregressive distributed lag technique to examine the nexus between housing affordability to capture the distinct characteristics of the sample countries and estimate various short- and long-run dynamics in the relationship between housing affordability and exchange rate.

Exchange rate appreciation improves housing affordability in the short run, whereas this connection tends to dissipate in the long run. Moreover, inflation can worsen housing affordability during turbulent times, such as the global financial crisis, in both the short and long run. Ignoring these changes in the relationship between exchange rates and housing affordability during turbulent times can lead to incorrect conclusions.

To the best of the authors’ knowledge, this study is the first to examine the association between exchange rates and housing affordability by demonstrating how these variables behave in high and low inflation regimes and turbulent times.

Construction waste reduction (CWR) plays a vital role in achieving sustainability in construction. A good CWR practice can result in optimizing material usage, conserving natural resources, limiting environmental pollution, protecting the environment and enhancing human health. In this regard, the purpose of the current study is to identify the most relevant organizational policies that aid in waste reduction and concurrently explores the congruent measures to be adopted during the construction process in the Indian high-rise building sector.

The research findings were obtained through a mixed- method approach. Content analysis was used to identify waste reduction measures (variables) targeting on the two domains of construction – “waste-efficient execution” and “waste – mitigating organizational policies.” Furthermore, the authors explored and documented the key measures from the identified waste reduction measures using the constraint value of the relative importance index. As the next step, the study listed the theoretical hypothesis based on expert interviews and tested the theory through confirmatory factor analysis.

The results revealed that “waste sensitive construction techniques and strategies” as the most significant category under the domain “Execution” with a path coefficient of 0.85. Concurrently, the study has also determined that “control procedures for budget, quality and resources” as the most effective organizational approach in reducing construction waste in the Indian building industry, with a path coefficient of 0.83.

The current research is context-sensitive to the Indian construction sector. It presents the stakeholder’s perspective on construction waste reduction and the relevant measures to be implemented to reduce construction waste in high-rise building projects in India. It can also act as a concordance for decision-makers to further focus on CWR management and aid in formulating policies suitable for the Indian context.

Although prior research has employed various variables to predict player churn, the dynamic evolution of the behavioral patterns of players has received limited attention. In this study, churn prediction models are developed by incorporating the progress level, in-game purchase, social interaction, behavioral pattern and behavioral variability (BV) of players in social casino games (SCGs). The study distinguishes churn prediction between two player groups: monetizers and non-monetizers.

This study employs three machine learning techniques—logistic regression, decision trees and random forests—using real-world player data from an SCG company to construct churn prediction models. Two experiments were conducted. In Experiment 1, BV was combined with four other variable categories to effectively predict churn behaviors across all players (n = 52,246). In Experiment 2, churn prediction models were developed separately for monetizers (n = 16,628) and non-monetizers (n = 35,618).

The findings from Experiment 1 indicate that incorporating BV significantly improves the overall performance of churn prediction models. Experiment 2 demonstrates that churn prediction models achieve better performance and predictive accuracy for monetizers and non-monetizers when BV is calculated over the 3-day to 7-day and 7-day to 14-day windows, respectively.

This study introduces BV as a novel variable category for churn prediction, emphasizing within-person variability and demonstrating its effectiveness in enhancing model performance. Churn prediction models were independently constructed for monetizers and non-monetizers, utilizing different time windows for variable extraction. This approach improves predictive performance and highlights key differences in critical variables influencing churn across the two player groups. The findings provide valuable insights into churn management strategies tailored for monetizers and non-monetizers.

This study aims to explore the development of trust in relation to security and privacy concerns, as well as the influence of perceived risk on the intention to use e-wallets. The research focused on the Colombian context because of its characterization as an underdeveloped financial system that has experienced considerable security and privacy violations in recent years. Additionally, this geographical area is relatively under-researched, and the target demographic for this investigation was Generation Z, given their pivotal role in driving the adoption of e-wallets.

Based on measurement scales that had already been tested in the academic literature on mobile payment systems, a questionnaire was developed and distributed electronically. A total of 424 responses were obtained from young Colombians. Structural equation modeling (SEM), specifically the PLS-SEM method, was used to process the data to study the explanatory and predictive power of the proposed model.

The findings revealed that security and privacy have a positive and significant effect on perceived trust, and that this at the same time has a positive and significant effect on attitude, perceived usefulness, perceived ease and intention to use, as well as a significant but negative effect on perceived risk. On the other hand, perceived risk showed an inverse, but not significant, relationship with intention to use.

This research explored the adoption of e-wallets by young people in Colombia, which has been widely claimed in the academic literature. In a turbulent context with a high distrust of financial institutions, as well as a change in digital money consumption patterns, it is critical to understand the factors that contribute to the adoption of mobile payment services. The findings, in addition to contributing to the academic debate, have important implications for e-wallet providers, as they offer information that allows designing strategies to attract and keep current and potential users. At the same time, the recommendations by the authors allow the design of tools, especially related to security and privacy, to improve their trust and build loyalty, thus contributing to the consolidation and development of the mobile payment system.

Este estudio explora el desarrollo de la confianza en relación con las preocupaciones sobre seguridad y privacidad, así como la influencia del riesgo percibido en la intención de utilizar monederos electrónicos. La investigación se centró en el contexto colombiano debido a su caracterización como un sistema financiero subdesarrollado que ha experimentado violaciones considerables de seguridad y privacidad en los últimos años. Además, esta área geográfica está relativamente poco investigada, y el público objetivo de esta investigación fue la Generación Z, dado su papel clave en la adopción de monederos electrónicos.

Basado en escalas de medición ya probadas en la literatura académica sobre sistemas de pago móvil, se desarrolló y distribuyó electrónicamente un cuestionario. Se obtuvieron un total de 424 respuestas de jóvenes colombianos. Se utilizó el modelado de ecuaciones estructurales, específicamente el método PLS-SEM, para procesar los datos y estudiar el poder explicativo y predictivo del modelo propuesto.

Nuestros hallazgos revelaron que la seguridad y la privacidad tienen un efecto positivo y significativo en la confianza percibida, y que esto, a su vez, tiene un efecto positivo y significativo en la actitud, la utilidad percibida, la facilidad percibida y la intención de uso, así como un efecto significativo pero negativo en el riesgo percibido. Por otro lado, el riesgo percibido mostró una relación inversa, pero no significativa, con la intención de uso.

Esta investigación exploró la adopción de monederos electrónicos por parte de los jóvenes en Colombia, un tema ampliamente mencionado en la literatura académica. En un contexto turbulento con alta desconfianza hacia las instituciones financieras, así como un cambio en los patrones de consumo de dinero digital, es crucial comprender los factores que contribuyen a la adopción de servicios de pago móvil. Nuestros hallazgos, además de contribuir al debate académico, tienen importantes implicaciones para los proveedores de monederos electrónicos, ya que ofrecen información que permite diseñar estrategias para atraer y retener a usuarios actuales y potenciales. Al mismo tiempo, nuestras recomendaciones permiten diseñar herramientas, especialmente relacionadas con la seguridad y la privacidad, para mejorar la confianza y fomentar la lealtad, contribuyendo así a la consolidación y desarrollo del sistema de pago móvil.

本研究探讨了与安全性和隐私问题相关的信任发展, 以及感知风险对使用电子钱包意图的影响。研究集中在哥伦比亚的背景下, 因为该国的金融系统被认为是欠发达的, 近年来经历了相当大的安全性和隐私侵犯问题。此外, 这一地理区域的研究相对较少, 本研究的目标人群为Z世代, 考虑到他们在推动电子钱包采纳中的关键作用。

基于已经在移动支付系统学术文献中测试过的测量尺度, 开发并电子分发了一份问卷。共获得了424份哥伦比亚年轻人的回应。使用结构方程建模中的PLS-SEM方法处理数据, 以研究所提出模型的解释力和预测力。

研究发现, 安全性和隐私对感知信任有显著正向影响, 同时, 感知信任对态度、感知有用性、感知易用性和使用意图也有显著正向影响, 并对感知风险有显著负向影响。另一方面, 感知风险与使用意图之间呈现出反向但不显著的关系。

本研究探讨了哥伦比亚年轻人对电子钱包的采纳, 这在学术文献中已有广泛讨论。在一个对金融机构高度不信任的动荡背景下, 以及数字货币消费模式的变化中, 理解促使移动支付服务采纳的因素至关重要。我们的研究结果不仅有助于学术讨论, 还对电子钱包提供商具有重要意义, 因为这些结果提供了信息, 有助于设计吸引和留住当前及潜在用户的策略。同时, 我们的建议有助于设计特别与安全性和隐私相关的工具, 以提高用户信任并建立忠诚度, 从而促进移动支付系统的巩固和发展。

The current study aims to examine if the internal marketing and employees’ personal traits can predict their green innovative behavior at the workplace.

A survey was conducted with 683 frontline employees working in four- and five-star hotels in Serbia. Zero-order bivariate correlations among variables and linear multiple regression were conducted to predict green innovative behavior based on internal marketing, personality traits and psychological capital. Binary genetic algorithms were used to segregate the subset of predictors that would be most suitable to describe variance in the outcome.

The results showed that internal communication, incentive and reward systems, work support, work environment, openness and creative self-efficacy were the most important predictors of almost all the phases of green innovative behavior.

The research showed that a multidimensional approach in analyzing green innovative behavior is necessary as some factors can be significant or not so significant predictors. Acknowledging that innovation is a multistage process, entailing distinct activities and requiring varied individual behaviors to accomplish each task, amplifies the importance of this inquiry. Employees’ personal characteristics have direct impact on green innovative behavior in hospitality. Further, the results gave an insight into the possible mix of elements of internal marketing that can be used for boosting employees’ green innovative behavior in hospitality. This is important as implementing effective internal marketing practices empowers organizations to motivate employees to invest discretionary efforts.

本研究旨在探讨内部营销和员工个人特质是否能预测他们在工作场所的绿色创新行为。

在塞尔维亚的四星和五星级酒店中, 对683名一线员工进行了调查。在变量之间进行了零阶双变量相关性和线性多元回归, 以预测基于内部营销、个性特质和心理资本的绿色创新行为。使用二元遗传算法(GAs)将适用于描述结果变异性的预测子集进行分离。

结果显示, 内部沟通、激励和奖励制度、工作支持、工作环境、开放性和创造力自效能是几乎所有绿色创新行为阶段的最重要的预测因素。

研究表明, 分析绿色创新行为需要采用多维度的方法, 因为某些因素可能是更或更少决定性的预测因素。承认创新是一个多阶段的过程, 涉及到不同的活动, 并要求采用不同的个体行为来完成每个任务, 这加强了对这一调查的重要性。员工的个人特征直接影响了酒店业的绿色创新行为。此外, 结果揭示了可以用于促进酒店业员工绿色创新行为的内部营销元素可能的混合。这是重要的, 因为实施有效的内部营销实践使组织能够激励员工投入可自由支配的努力。

El presente estudio examina si el marketing interno y los rasgos de personalidad de los empleados pueden predecir su comportamiento innovador ecológico en el lugar de trabajo.

Se realizó una encuesta a 683 empleados de primera línea que trabajan en hoteles de cuatro y cinco estrellas en Serbia. Se llevaron a cabo correlaciones bivariadas de orden cero y regresiones lineales múltiples (LM) para predecir el comportamiento innovador ecológico en función del marketing interno, los rasgos de personalidad y el capital psicológico. Se utilizaron algoritmos genéticos binarios (AGs) para segregar el subconjunto de predictores más adecuado para describir la variabilidad en el resultado.

Los resultados mostraron que la comunicación interna, los sistemas de incentivos y recompensas, el apoyo en el trabajo, el entorno laboral, la apertura y la autoeficacia creativa eran los predictores más importantes en casi todas las fases del comportamiento innovador ecológico.

La investigación demostró que es necesario un enfoque multidimensional para analizar el comportamiento innovador ecológico, ya que algunos factores pueden o no ser predictores significativos. Reconocer que la innovación es un proceso de múltiples etapas, que implica actividades distintas y requiere comportamientos individuales variados para realizar cada tarea, amplifica la importancia de esta investigación. Las características personales de los empleados influyen directamente en el comportamiento innovador ecológico en la industria hotelera. Además, los resultados ofrecen una visión de la posible combinación de elementos de marketing interno que se pueden utilizar para impulsar el comportamiento innovador ecológico de los empleados en la hotelería. Esto es importante ya que la implementación de prácticas eficaces de marketing interno permite a las organizaciones motivar a los empleados para que inviertan esfuerzos discrecionales.

The purpose of this paper is to identify the influence of homophily and social identity in eWOM adoption and influence on music consumption in streaming platforms. The study also proposes a framework for eWOM influence on product consumption.

Data were collected through an electronic questionnaire with a total of 524 valid responses. A partial least square methodology was used to approach the data analysis.

The findings indicate that both homophily and social identity have an influence on eWOM effect. Additionally, homophily shows influence on social identity being an important value to the total influence. It is also confirmed how eWOM has direct influence on music consumption.

Social information of consumers becomes more relevant than ever, as the results contribute to highlight its importance as a message adoption influencer and product consumption driver.

This study contributes to social communication theory by identifying homophily and social identity as valuable assets during eWOM generation. The research brings a new angle to social identity theory in the social network environment and influences eWOM adoption in music streaming consumption.

El propósito de este estudio es identificar la influencia de la homofilia y la identidad social en la adopción de eWOM y su influencia en el consumo de música en plataformas de streaming. El estudio también propone un marco para la influencia de la eWOM en el consumo de productos.

Los datos se recopilaron a través de un cuestionario electrónico con un total de 524 respuestas válidas. Se utilizó una metodología de Mínimos Cuadrados Parciales para abordar el análisis de datos.

Los hallazgos indican que tanto la homofilia como la identidad social tienen una influencia en el efecto de la eWOM. Además, la homofilia muestra influencia en la identidad social siendo un valor importante para la influencia total. También se confirma cómo la eWOM tiene influencia directa en el consumo de música.

Este estudio contribuye a la teoría de la comunicación social identificando la homofilia y la identidad social como activos valiosos durante la generación de eWOM. La investigación aporta un nuevo enfoque a la teoría de la identidad social en el entorno de las redes sociales e influye en la adopción de eWOM en el consumo de música en streaming.

La información social de los consumidores se vuelve más relevante que nunca, ya que los resultados contribuyen a resaltar su importancia como influenciador en la adopción de mensajes y como impulsor del consumo de productos.

本文旨在确定同质性和社会认同对电子口碑在音乐流媒体平台上的采纳的影响。研究还提出了一个关于eWOM对产品消费影响的框架。

通过电子问卷收集了524份有效回复, 并采用了偏最小二乘法对数据进行分析。

研究结果显示, 同质性和社会认同对eWOM效果产生影响。此外, 同质性对社会认同产生影响, 对总体影响具有重要价值。另外, 研究还确认了eWOM对音乐消费的直接影响。

本研究通过确认同质性和社会认同在eWOM生成过程中的重要价值, 为社交传播理论做出了重要贡献。研究为社交网络环境下的社会认同理论提供了新的视角,并对音乐流媒体消费中的eWOM采纳产生了影响。

在当前社会环境下, 消费者的社会信息比以往任何时候都更加重要。本研究的结果有助于凸显社会信息在信息采纳和产品消费方面的重要性, 进一步强调了其作为影响因素和驱动力的重要性。

Integrating artificial intelligence and quantitative investment has given birth to various agricultural futures price prediction models suitable for nonlinear and non-stationary data. However, traditional models have limitations in testing the spatial transmission relationship in time series, and the actual prediction effect is restricted by the inability to obtain the prices of other variable factors in the future.

To explore the impact of spatiotemporal factors on agricultural prices and achieve the best prediction effect, the authors innovatively propose a price prediction method for China's soybean and palm oil futures prices. First, an improved Granger Causality Test was adopted to explore the spatial transmission relationship in the data; second, the Seasonal and Trend decomposition using Loess model (STL) was employed to decompose the price; then, the Apriori algorithm was applied to test the time spillover effect between data, and CRITIC was used to extract essential features; finally, the N-Beats model was selected as the prediction model for futures prices.

Using the Apriori and STL algorithms, the authors found a spillover effect in agricultural prices, and past trends and seasonal data will impact future prices. Using the improved Granger causality test method to analyze the unidirectional causality relationship between the prices, the authors obtained a spatial effect among the agricultural product prices. By comparison, the N-Beats model based on the spatiotemporal factors shows excellent prediction effects on different prices.

This paper addressed the problem that traditional models can only predict the current prices of different agricultural products on the same date, and traditional spatial models cannot test the characteristics of time series. This result is beneficial to the sustainable development of agriculture and provides necessary numerical and technical support to ensure national agricultural security.