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1 – 10 of 72Xiaojie Xu and Yun Zhang
The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important…
Abstract
Purpose
The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.
Design/methodology/approach
The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.
Findings
The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.
Originality/value
The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.
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This study aims to explore the moderating effects of strategy on the relationship between working capital management (WCM) and profitability.
Abstract
Purpose
This study aims to explore the moderating effects of strategy on the relationship between working capital management (WCM) and profitability.
Design/methodology/approach
A data sample of 72,444 firm-year observations of US-listed firms during 2000–2020 was used. The research hypotheses were tested using a panel regression analysis and an appropriate research instrument that signifies a firm’s strategic positioning.
Findings
The prospecting (defending) strategy has a decreasing (increasing) moderating effect on the relationship between WCM and profitability. The empirical findings are not affected by the level of earnings management, the presence of motives to meet earnings targets or the intensity of unreported intangible assets. Additionally, the reported empirical results remain robust within the context of propensity score matching regression analysis, in the presence of nonlinear effects of WCM on profitability, when alternative measures of WCM are used, and between firms with an increase or decrease in future profitability or different levels of efficiency on net WCM investments.
Research limitations/implications
This study may stimulate future research exploring the moderating effects of various variables on the relationship between WCM and operating performance.
Practical implications
The findings highlight the importance of strategy for improving the performance evaluation of WCM policies and the prediction accuracy of the consequences of a strategy on short-term operating performance.
Originality/value
Prior empirical research has documented either a negative or positive relationship between WCM and profitability, which implies the presence of moderating effects of various factors. This study provides empirical evidence of the moderating effects of strategy on the relationship between WCM and profitability.
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Nannan Xi, Juan Chen, Filipe Gama, Henry Korkeila and Juho Hamari
In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in…
Abstract
Purpose
In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.
Design/methodology/approach
This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.
Findings
Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.
Originality/value
This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.
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Juan Camilo Carvajal Builes, Idaly Barreto and Carolina Gutiérrez de Piñeres
This study aims to describe and analyze the differences in the linguistic styles of honest and dishonest stories.
Abstract
Purpose
This study aims to describe and analyze the differences in the linguistic styles of honest and dishonest stories.
Design/methodology/approach
This paper uses a descriptive study with a multivariate analysis of linguistic categories according to the story. The research analyzed 37 honest stories and 15 dishonest stories produced during actual legal proceedings through software Linguistic Inquiry and Word Count (LIWC).
Findings
The authors find that individuals who engage in deception use a different number of words when they narrate facts. The results suggest a need for additional investigation of the linguistic style approach because of its high applicability and detection accuracy. This approach should be complemented by other types of verbal, nonverbal and psychophysiological deception detection techniques.
Research limitations/implications
Among the limitations, the authors consider length of the stories should be considered and scarce scientific literature in Spanish to compare with outcomes in English.
Practical implications
This research highlights the relevance to include linguistic style in real contexts to differentiate honest and dishonest stories due to objectivity and agility to implement.
Social implications
Understanding deception as a social behaviour and its psychological processes associated are elements that contribute to people and justice to comprehend it.
Originality/value
Analyzing real statements and discriminate differences in linguistic style, contribute to understand deeply this important behaviour to propose new methodologies and theories to explain it.
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Juan Luis Nicolau, Zheng Xiang and Dan Wang
This paper aims to investigate the links between daily review sentiment and the hotel performance measures of occupancy rate (OR), average daily rate (ADR) and revenue per…
Abstract
Purpose
This paper aims to investigate the links between daily review sentiment and the hotel performance measures of occupancy rate (OR), average daily rate (ADR) and revenue per available room (RevPAR).
Design/methodology/approach
The authors conducted review sentiment analyses in three moments (−1, −7 and −14 days) before arrival time using a data set of budget hotel performance and online reviews. The aim was to identify the effect of review sentiment in the budget hotel market on the three performance metrics.
Findings
Daily sentiment positively affects ADR and negatively affects OR and RevPAR, but only up to a certain threshold, after which the trend reverses. Prices increase with the level of sentiment, and high prices lead to low OR and RevPAR only when the sentiment scores are low. When they are high, they are associated with low rates, which lead to high OR and RevPAR.
Research limitations/implications
Daily review sentiment can be viewed as a valuable “barometer” indicating a hotel’s daily operational effectiveness. Daily sentiment can thus allow hotel managers to adjust their dynamic pricing strategies more accurately.
Originality/value
This study identifies daily sentiment as an alternative predictor of hotel performance. In addition to the roles of valence and volume in the decision-making process, the authors found that daily review sentiment can be an “in-the-moment” factor with a high impact, encouraging consumers to complete their transactions. This study suggests that aggregated measures such as the total number of reviews and overall ratings of the hotel should not be the sole consideration in reputation management.
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Mauricio Pérez Giraldo, Mauricio Vasquez, Alejandro Toro, Robison Buitrago-Sierra and Juan Felipe Santa
This paper aims to develop a stable gel-type lubricant emulating commercial conditions. This encompassed rheological and tribological assessments, alongside field trials on the…
Abstract
Purpose
This paper aims to develop a stable gel-type lubricant emulating commercial conditions. This encompassed rheological and tribological assessments, alongside field trials on the Medellín tram system.
Design/methodology/approach
The gel-type lubricant with graphite and aluminum powder is synthesized. Rheological tests, viscosity measurements and linear viscoelastic regime assessments are conducted. Subsequently, tribological analyses encompassing four-ball and twin disc methods are executed. Finally, real-world testing is performed on the Medellín tram system.
Findings
An achieved lubricant met the stipulated criteria, yielding innovative insights into the interaction of graphite and aluminum powder additives under varying tests.
Originality/value
Novel findings are unveiled regarding the interaction of graphite and aluminum powder additives in tribological, rheological and real-world trials. In addition, the wear behavior of polymers is observed, along with the potential utilization of such additives in tramway systems.
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Mousumi Bose, Lilly Ye and Yiming Zhuang
Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning…
Abstract
Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning technique, generative adversarial networks (GANs). GANs are a type of deep learning architecture capable of generating new data similar to the training data that were used to train it, and thus, it is designed to learn a generative model that can produce new samples. GANs have been used in multiple marketing areas, especially in creating images and video and providing customized consumer contents. Through providing a holistic picture of GANs, including its advantage, disadvantage, ethical considerations, and its current application, the study attempts to provide business some strategical orientations, including formulating strong marketing positioning, creating consumer lifetime values, and delivering desired marketing tactics in product, promotion, pricing, and distribution channel. Through using GANs, marketers will create unique experiences for consumers, build strategic focus, and gain competitive advantages. This study is an original endeavor in discussing GANs in marketing, offering fresh insights in this research topic.
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Giulia Pavone and Kathleen Desveaud
This chapter provides an overview of the strategic implications of chatbot use and implementation, including potential applications in marketing, and factors affecting customer…
Abstract
This chapter provides an overview of the strategic implications of chatbot use and implementation, including potential applications in marketing, and factors affecting customer acceptance. After presenting a brief history and a classification of conversational artificial intelligence (AI) and chatbots, the authors provide an in-depth review at the crossroads between marketing, business, and human–computer interaction, to outline the main factors that drive users' perceptions and acceptance of chatbots. In particular, the authors describe technology-related factors and chatbot design characteristics, such as anthropomorphism, gender, identity, and emotional design; context-related factors, such as the product type, task orientation, and consumption contexts; and users-related factors such as sociodemographic and psychographic characteristics. Next, the authors detail the strategic importance of chatbots in the field of marketing and their impact on consumers' perceived service quality, satisfaction, trust, and loyalty. After discussing the ethical implications related to chatbots implementation, the authors conclude with an exploration of future opportunities and potential strategies related to new generative AI technologies, such as ChatGPT. Throughout the chapter, the authors offer theoretical insights and practical implications for incorporating conversational AI into marketing strategies.
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Hongxiao Yu, Haemoon Oh and Kuo-Ching Wang
This study aims to examine the underlying emotional process that explains how context-specific stimuli involved in virtual reality (VR) destinations translate into presence…
Abstract
Purpose
This study aims to examine the underlying emotional process that explains how context-specific stimuli involved in virtual reality (VR) destinations translate into presence perceptions and behavioral intentions.
Design/methodology/approach
In total, 403 potential tourists participated in a self-administered online survey after they watched a randomly assigned VR tour. The Lavaan package in R software was used to conduct structural equation analysis and examine the proposed theoretical framework.
Findings
The results reveal that media content consisting of informativeness, aesthetics and novelty was positively related to users’ sense of presence in a VR tour. The effect of media content on presence was partially mediated by emotional arousal.
Practical implications
Managers and VR designers can create an emotive virtual tour that contributes to the user’s sense of presence to promote attraction to the target destination. The VR content needs to be informative, aesthetic and novel, which can excite users during the VR tour, portray virtual destinations clearly and eventually influence potential tourists’ visit intentions.
Originality/value
Research on the emotional mechanism to generate presence is still in its infancy. This study integrates presence theory into a conceptual framework to explore how media content influences presence and decision-making through the emotional mechanism.
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Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary…
Abstract
Purpose
Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary information disseminators is limited. This paper aims to bring an in-depth understanding of voluntary disseminators by answering the following questions: (1) What is the underlying mechanism by which some users are more enthusiastic to voluntarily forward content of interest? (2) How to identify them? We propose a theoretical model based on the Elaboration-Likelihood Model (ELM) and examine three types of factors that moderate the effect of preference matching on individual forwarding behavior, including personal characteristics, tweet characteristics and sender–receiver relationships.
Design/methodology/approach
Via Twitter API, we randomly crawled 1967 Twitter users' data to validate the conceptual framework. Each user’s original tweets and retweeted tweets, profile data such as the number of followers and followees and verification status were obtained. The final corpus contains 163,554 data points composed of 1,634 valid twitterers' retweeting behavior. Tweets produced by these core users' followees were also crawled. These data points constitute an unbalanced panel data and we employ different models — fixed-effects, random-effects and pooled logit models — to test the moderation effects. The robustness test shows consistency among these different models.
Findings
Preference matching significantly affects users' forwarding behavior, implying that SNS users are more likely to share contents that align with their preferences. In addition, we find that popular users with lots of followers, heavy SNS users who author tweets or forward other-sourced tweets more frequently and users who tend to produce longer original contents are more enthusiastic to disseminate contents of interest. Furthermore, interaction strength has a positive moderating effect on the relationship between preference matching and individuals' forwarding decisions, suggesting that users are more likely to disseminate content of interest when it comes from strong ties. However, the moderating effect of perceived affinity is significantly negative, indicating that an online community of individuals with many common friends is not an ideal place to engage individuals in sharing information.
Originality/value
This work brings about a deep understanding of users' voluntary forwarding behavior of content of interest. To the best of our knowledge, the current study is the first to examine (1) the underlying mechanism by which some users are more likely to voluntarily forward content of interest; and (2) how to identify these potential voluntary disseminators. By extending the ELM, we examine the moderating effect of tweet characteristics, sender–receiver relationships as well as personal characteristics. Our research findings provide practical guidelines for enterprises and government institutions to choose voluntary endorsers when trying to engage individuals in information dissemination on SNS.
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