Search results

This study examines how the visual cues (i.e. positioning in cobranding advertising) influence the luxury evaluation.

Through four experiments in different contexts, this study investigates the effects of the positioning of two brands in cobranding on luxury evaluation, the moderating role of product category and the mediating role of benefit understanding.

This study finds that the positioning of two brands in cobranding affects luxury evaluation. Specifically, vertical positioning benefits consumers’ attitude toward luxury compared with horizontal positioning. Results also elucidate that such an effect depends on the product category; that is, the effect of positioning on luxury only exists when the cobranded product belongs to the core (vs non-core) category of luxury. The benefit understanding explains the effects of the positioning and product category on the luxury attitude.

This study contributes to the literature on luxury and cobranding by exploring the visual cues at the marketing communication level influencing the evaluation of luxury brands.

The findings provide important managerial guidelines for enhancing luxury cobranding effectiveness.

This study proposes positioning in cobranding advertisements as one of the antecedents affecting luxury cobranding evaluation. Accordingly, this study adopts a new perspective on visual perception, based on conceptual metaphor theory, which advances the theoretical and empirical knowledge of luxury cobranding.

This study examines the antecedents and outcomes of using mobile fintech applications, including mobile banking, mobile payments, mobile transfer and mobile financial money management tools.

This paper examines the antecedents (i.e. financial education and financial literacy) and outcomes (i.e. desirable financial behaviors and financial well-being) of the utilization of mobile fintech. Using data from the 2018 National Financial Capability Study and structural equation modeling techniques, this study provides empirical evidence to show significant direct and indirect relationships among these factors.

The structural equation modeling results revealed that financial education was positively associated with both financial literacy and mobile fintech utilization. Interestingly, financial literacy was negatively associated with mobile fintech utilization and served as a negative mediator between financial education and mobile fintech utilization, while it positively correlated with desirable financial behaviors, enhancing financial well-being. Utilization of mobile fintech was negatively associated with desirable financial behaviors and indirectly and negatively associated with financial well-being. The alternative model highlighted a direct and negative association between mobile fintech usage and financial well-being, and a direct positive association between financial literacy and financial well-being.

This study makes contributions to the literature on financial well-being by examining pathways of antecedents and outcomes of mobile fintech utilization. The findings provide new insights into the rapid evolution of mobile fintech innovations and provide important policy and practical implications.

This study aims to develop a modelling framework of housing supply dynamics within the context of urban microsimulation systems. Housing markets have witnessed substantial investigation over recent decades, predominantly concerning residential demand. However, comparatively limited attention has been directed towards comprehending the housing supply dynamics. Housing policy disconnects with the developers’ market behaviours, which leads to significant mismatch between the housing construction and affordable housing needs of the population. Research attention should be made in comprehending the residential construction market activities. To address this gap, this study developed an autoregressive distributed lag (ARDL) model and analyzed the temporal evolution of housing construction.

An ARDL model was developed to address the issue of temporal modelling of the housing supply. An empirical study was conducted in the Greater Toronto and Hamilton Area (GTHA) based on a longitudinal housing starts data set from 1998 to 2020. The model integrates diverse variables, including macroeconomic conditions, property development costs, dwelling prices and opportunity costs. Notably, the model captures both the path-dependent effects stemming from supply market fluctuations and the temporal lag effect of influential factors.

The findings reveal that the supply-side’s responsiveness to market condition alterations may span up to 18 months. The model has reasonable and satisfying performance in fitting the observed starts. The methodological foundations laid will facilitate future modelling of housing supply dynamics.

This study innovatively separated the modelling of housing supply within the context of urban microsimulation, into two parts, the modelling of housing starts and completion. The housing starts are determined in a complex and regressive process influenced by both the micro-economic environment and the construction cost and housing market trends. Through the temporal modelling method, this study captures how long it would take for the housing supply to respond to multiple factors and provides insight for urban planners in regulating the housing market and leveraging various policies to influence the housing supply.

The purpose of this research is to conceptualize, define and measure resource orchestration capabilities of R&D teams pursuing advanced scientific research and technological innovation at public-funded R&D organizations in India.

A series of five mutually exclusive studies were designed over two years to develop and validate the ROCI scale within public research and development (R&D) organizations pursuing advanced scientific research and technological development in India. The first three studies address the refinement, reduction and rationalization of items for measuring the ROCI construct. The next study explores the factor structure underlying the ROCI construct whereas the subsequent one confirms the three-factor structure within empirical settings.

The resource orchestration capability towards innovation (ROCI) construct reflected through three sub-dimensions namely – adaptive structuring capability (ASC), synergistic leveraging capability (SLC) and decentralized decision-making capability (DDC), each loaded with their respective items can be used for capability measurement in public-funded R&D organizations.

R&D managers can use this ROCI scale to measure, monitor and improve the innovation-oriented resource orchestration capabilities of their R&D teams and help them improve their innovation performance.

This research contributes to the extant literature on resource orchestration for innovation management in three unique and original ways – theoretically-grounded conceptualization, empirical measurement and rigorous validation through multiple studies conducted in public-funded R&D organizations in India.

Competitiveness is an important personality trait that has been studied in various disciplines and has been shown to predict critical work outcomes at the individual level. Despite this, the role of competitiveness in groups and teams has received scant attention amongst organizational researchers. Aiming to promote future research on the role of competitiveness as both an adaptive and maladaptive trait – particularly in the context of work – the authors review competitiveness and its effects on individual and team stress and Well-Being, giving special attention to the processes of cohesion and conflict and situational moderators. The authors illustrate a dynamic multilevel model of individual and team difference factors, competitive processes, and individual and team outcomes to highlight competitiveness as a consequential occupational stressor. Furthermore, the authors discuss the feedback loops that inform the different factors, highlight important avenues for future research, and offer practical solutions for managers to reduce unhealthy competition.

This study aims to apply the predictive processing theory to examine the influence of artificial intelligence (AI)-driven robotic performers on audience emotions and the audience’s resulting electronic word-of-mouth (eWOM) behaviors during tourism service encounters.

Using a quantitative research methodology, survey responses from 339 regular customers of performing arts in tourism destinations were analyzed. The respondents were recruited through Prolific, a professional data collection platform. SPSS 23.0 was used for the preliminary analysis, from which a research model to achieve the aim was proposed. SmartPLS 3 was used for partial least squares structural equation modeling to test the model.

Interactive and novel robotic performances significantly encouraged the consumers to share their experiences online, thereby enhancing eWOM. However, melodic resonance had no significant impact on eWOM intentions. The consumers’ emotional responses fully mediated the relationship of the novelty and interactivity of the performances to the consumers’ eWOM intentions but did not mediate the relationship of the musical elements to their eWOM intentions.

This study enriches the understanding of how AI-driven performances impact consumers’ emotional engagement and sharing behaviors. It extends the application of the predictive processing theory to the domain of consumer behavior, offering valuable insights for enhancing audience engagement in performances through technological innovation.

本研究旨在运用预测处理理论, 考察人工智能（AI）驱动的机器人表演对观众情感及其在旅游服务接触中的电子口碑（eWOM）行为的影响。。

采用定量研究方法, 分析了339名经常观看旅游景点表演艺术的常客的调查问卷。受访者通过专业数据收集平台Prolific招募。初步分析使用SPSS 23.0进行, 从中提出了实现研究目标的研究模型。使用SmartPLS 3进行偏最小二乘结构方程模型测试该模型。

互动性和新颖性的机器人表演显著鼓励消费者在线分享他们的体验, 从而增强电子口碑。然而, 旋律共鸣对电子口碑意图没有显著影响。消费者的情感反应完全中介了表演的新颖性和互动性与消费者电子口碑意图之间的关系, 但没有中介音乐元素与电子口碑意图之间的关系。

本研究丰富了对AI驱动表演如何影响消费者情感参与和分享行为的理解。将预测处理理论的应用扩展到消费者行为领域, 为通过技术创新增强观众参与度提供了宝贵的见解。

This study presents the impact of Economic Policy Uncertainty (EPU)-induced Trade Supply Chain Vulnerability (TSCV) on the Small and Medium-Sized Enterprises (SMEs) in India by leveraging the World Bank Enterprise Survey data for 2014 and 2022. Applying econometric techniques, it examines firm size’ influence on productivity and trade participation, providing insights for enhancing SME resilience and trade participation amid uncertainty.

The econometric techniques focus on export participation, along with variables such as total exports, firm size, productivity, and capital intensity. It addresses crucial factors such as the direct import of intermediate goods and foreign ownership. Utilizing the Cobb-Douglas production function, the study estimates Total Factor Productivity, mitigating endogeneity and multicollinearity through a two-stage process. Besides, the study uses a case study of North Indian SMEs engaged in manufacturing activities and their adoption of mitigation strategies to combat unprecedented EPU.

Results reveal that EPU-induced TSCV reduces exports, impacting employment and firm size. Increased productivity, driven by technological adoption, correlates with improved export performance. The study highlights the negative impact of TSCV on trade participation, particularly for smaller Indian firms. Moreover, SMEs implement cost-based, supplier-based, and inventory-based strategies more than technology-based and risk-based strategies.

Policy recommendations include promoting increased imports and inward foreign direct investment to enhance small firms’ trade integration during economic uncertainty. Tailored support for smaller firms, considering their limited capacity, is crucial. Encouraging small firms to engage in international trade and adopting diverse SC mitigation strategies associated with policy uncertainty are vital considerations.

This study explores the impact of EPU-induced TSCV on Indian SMEs’ trade dynamics, offering nuanced insights for policymakers to enhance SME resilience amid uncertainty. The econometric analysis unveils patterns in export behavior, productivity, and factors influencing trade participation during economic uncertainty.

This study aims to assess carbon emissions in urban aged residential buildings in Qingdao, Shandong Province, constructed prior to 2000, and to evaluate retrofitting and rebuilding strategies for potential carbon reduction.

Field investigations and literature reviews were conducted to identify key factors influencing carbon emissions, such as shape coefficient, window-to-wall ratio and envelope structure. A combination of generalization and mathematical statistical methods was used to classify buildings based on construction year, form, structural type and energy-saving goals. Cluster analysis was employed to extract six typical building models.

Results demonstrate that building form complexity positively correlates with carbon emissions per unit area, while longer lifespans reduce emission intensity. Retrofitting exhibits shorter carbon payback periods (1.62–3.92 years) than rebuilding (18.7–49.94 years), indicating superior environmental performance. Pre-1986 buildings are advised for demolition/rebuilding due to limited retrofit benefits. For 1986–1995 buildings, retrofitting is recommended if structurally viable. Post-1996 buildings favor retrofitting over new construction for its shorter payback and lower emissions, enhancing long-term carbon reduction.

This study contributes to the understanding of carbon emissions in urban aged residential buildings by considering various factors and providing specific recommendations for retrofitting and rebuilding strategies tailored to different construction periods. Additionally, it highlights the importance of building form complexity and remaining lifespan in determining carbon emissions, offering insights for sustainable urban development and carbon reduction initiatives.

This paper aims to measure and unveil the relationship between customer satisfaction and efficiency levels in the most relevant Brazilian airports.

The authors utilize a two-stage network DEA (data envelopment analysis) and AHP (analytic hierarchy process) model as the cornerstones of the study. The first stage of the network productive structure focuses on examining the infrastructure efficiency of the selected airports, while the second stage assesses their business efficiency.

Although the results indicate that infrastructure and business efficiency levels are heterogeneous and widely dispersed across airports, controlling the regression results with different contextual variables suggests that the impact of efficiency levels on customer satisfaction is mediated by a set of socio-economic and demographic (endogenous) and regulatory (exogenous) variables. Furthermore, encouraging investment in airports is necessary to achieve higher infrastructural efficiency and scale efficiency, thereby improving customer satisfaction.

There is a scarcity of studies examining the relationships among customer satisfaction, privatization and airport efficiency, particularly in developing countries like Brazil.

This study proposes the novel construct of digital transformation anxiety and investigates its effect, which is mediated by absorptive capacity and dynamic capability, on digital innovation performance.

This study conducted a questionnaire survey among Taiwanese manufacturing and service companies to verify the research framework. A total of 130 valid responses were collected and analyzed using partial least squares structural equation modeling (PLS-SEM) and bootstrapping to test direct and mediation effects, respectively.

Digital transformation anxiety negatively affects absorptive capacity and dynamic capability, whereas absorptive capacity and dynamic capability positively affect digital innovation performance. Dynamic capability more strongly mediates the association between digital transformation anxiety and digital innovation performance than absorptive capacity. Additionally, digital transformation anxiety does not negatively affect digital innovation performance. Finally, manufacturing companies had significantly higher levels of digital transformation anxiety than service companies.

This study proposes the novel construct of digital transformation anxiety to address a gap in the literature. Digital transformation anxiety leads companies to adopt unnecessarily conservative practices, preventing them from flexibly responding to technological advances. This insight highlights the negative effect of such anxiety on absorptive capacity and dynamic capability, extending the application of path dependency theory to companies. The findings underscore the value of enhancing dynamic capability and reallocating resources to foster digital innovation. The study identified and explored the concept of digital transformation anxiety and extended the perspective of dynamic capability to include digital transformation and digital innovation.

The current findings indicate that digital transformation anxiety does not substantially affect digital innovation performance in Taiwanese companies. Consequently, Taiwanese companies should focus on developing their absorptive capacity and dynamic capability to enhance digital innovation.

The study proposes the novel construct of digital transformation anxiety and explores its effect on business units. It presents a pioneering framework derived from path dependence theory and the perspective of dynamic capability.