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Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

It is widely evident that trust and commitment are important pillars for strengthening the relationship between financial service firms and their customers. However, it has not been explored how the service quality, perceived cost and role of agents are important for financial service firms. To overcome this gap, this study aims to investigate the role of service quality, perceived cost and the role of agents as the commitment–trust factors in the financial insurance service (Takaful) in Malaysia, enhancing customer satisfaction.

The study follows a quantitative design in which primary data was collected using a survey instrument. The measurement instrument was adapted from the previous research, and data were collected from 264 customers of the Takaful financial service organizations in Malaysia. The data were analyzed using variance-based structural equational modeling in Smart-PLS software.

This research has revealed several useful insights that demonstrate a significant impact on service quality, perceived cost and the agents’ role in forging close relationships with their customers. Corporate image has a moderating role in relationships and has significantly impacted takaful insurance companies. The results imply that regardless of the corporate image of the financial service organizations, customers are concerned about the prices and the quality of the agents’ services.

In this study, only the predictors such as service quality, perceived costs and agents’ roles as trust–commitment factors were examined to determine customer satisfaction. Other investigations are highly recommended, such as value co-creation in takaful, takaful customer experience and takaful trust. This study offers insights to takaful insurance companies on how to keep up a positive corporate image, which will boost their trust–commitment factors and ultimately increase customer satisfaction.

By presenting commitment–trust factors and company image in an identifiable framework, the current study has expanded the discussion on takaful financial insurance services. The methodology is developed and rigorously tested to gauge customer satisfaction in takaful financial service organizations’ context.

The purpose of this study is to develop a model that accurately forecasts hotel room cancelations and further determines the key cancelation drivers.

Predictive modeling, specifically the machine learning methods, is used to forecast room cancelations and identify the main cancelation factors.

By using three different classification algorithms, this study demonstrates that hotel room cancelation can be accurately predicted using XGBoost, as well as the ensemble method involving Support Vector Machine, Random Forest and XGBoost.

This study attempted to forecast hotel room cancelations by applying a relatively new method, machine learning. By implementing predictive modeling, one of the most emerging and innovative research methods, this study ultimately provides prediction suggestions in various aspects and levels for hotel management operations.

本研究旨在开发一个能够准确预测酒店客房取消的模型, 并进一步确定主要的取消因素。

采用预测建模, 具体来说是机器学习方法, 来预测客房取消, 并识别主要的取消因素。

通过使用三种不同的分类算法, 本研究表明使用XGBoost以及涉及支持向量机、随机森林和XGBoost的集成方法可以准确预测酒店客房取消。

本研究尝试通过应用相对较新的方法, 即机器学习, 来预测酒店客房取消。通过实施预测建模, 这是目前新兴和创新的研究方法之一, 本研究最终为酒店管理运营在各个方面和层面提供了预测建议。

The purpose of this study is to extend sales control research to inside sales. Aside from a few notable exceptions (Conde et al., 2022) much of the sales control literature has focused on a single control mechanism rather than a sales control portfolio perspective. The authors add multiple layers to Conde et al. (2022) by capturing secondary operational data and manager interviews to access sales control theory in practice.

With operational data from a Fortune 100 financial services company and sales manager interviews, the authors present evidence that managers apply a portfolio of controls to ensure sales agents’ overall performance.

Findings support that cultural controls have a greater influence on overall performance than a focus solely on process and outcome controls. Inside sales managers can generate better results when they focus on creating an employee-centric culture rather than controlling sales agents with formal sales controls.

This study extends sales control research by examining inside sales managers’ formal and informal sales controls. Historically, inside sales had sales leaders balance a myriad of sales controls grounded in strict oversight. With a few notable exceptions, the limited inside sales control research provides the opportunity to display an inside sales manager’s need to jointly focus on operational results and sales outcomes, illustrating the importance of cultural controls compared to other sales process and outcome controls. This research considerably extends sales controls research by focusing on inside sales.

This study aims to examine hotel guests’ acceptance of technology agency – the extent to which they would let artificial intelligence (AI)-based systems make decisions for them when staying in hotels. The examination was conducted through the prism of several antecedents of acceptance of technology agency, including perceived ethics, benefits, risks and convenience orientation.

A thorough literature review provided the foundation of the structural model, which was tested using confirmatory factor analysis, followed by structural equation modeling. Data were collected from 400 US hotel guests.

The most important determinant of acceptance of technology agency was perceived ethics, followed by benefits. Risks of using AI-based systems to make decisions for consumers had a negative impact on acceptance of technology agency. In addition, perceived loss of competence and unpredictability had relatively strong impacts on risks.

The results provide a conceptual foundation for research on systems that make decisions for consumers. As AI is increasingly incorporated in the business models of hotel companies to make decisions, ensuring that the decisions are perceived as ethical and beneficial for consumers is critical to increase the utilization of such systems.

Most research on AI in hospitality is either conceptual or focuses on consumers’ intentions to stay in hotels that may be equipped with AI technologies. Occupying a unique position within the literature, this study discusses the first time AI-based systems that make decisions for consumers. The value of this study stems from the examination of the main concept of technology agency, which was never examined in hospitality.

The aim of this paper is twofold. First, it seeks to understand how different forms of anthropomorphism, namely verbal and visual, can enhance or detract from the subjective well-being of consumers and their co-creation behaviors whilst collaborating with artificial intelligence (AI) service agents. Second, it seeks to understand if AI anxiety and trust in message, function as primary and secondary consumer appraisals of collaborating with AI service agents.

A conceptual model is developed using the theories of the uncanny valley and cognitive appraisal theory (CAT) with three hypotheses identified to guide the experimental work. The hypotheses are tested across three experimental studies which manipulate the level of anthropomorphism of AI.

Results demonstrate that verbal and visual anthropomorphism can assist consumer well-being and likelihood of co-creation. Further, this relationship is explained by the mediators of anxiety and trust.

The empirical results and theorizing suggest verbal anthropomorphism should be present (absent) and paired with low (high) visual anthropomorphism, which supports the “uncanny valley” effect. A moderated mediation relationship is established, which confirms AI anxiety and trust in a message as mediators of the AI service agent anthropomorphism-consumer subjective well-being/co-creation relationship. This supports the theorizing of the conceptual model based on the “uncanny valley” and CAT.

This paper addresses a gap in task performance research, with a focus on supply chain operations, by exploring the role that defensive pessimism (DP)—a phenomenon sparsely studied in supply chain literature—has in the workplace. It investigates the roles that task complexity, perceptions of control and employee situatedness in the workplace play as predictors of DP, as well as addresses the relationship between defensive pessimism and supply chain performance.

Five hypotheses are developed and empirically tested employing the data-generating method, Monte Carlo simulation and then applying factor analysis and structural equation modeling (SEM) to survey data from practitioner members of the Council of Supply Chain Management Professionals.

The results reveal that task complexity and external locus of control heighten perceptions among employees that task completion could be outside their locus of control. The increased tendency to be defensively pessimistic about workplace commitments negatively impacts supply chain performance. This study found that task complexity and external locus of control encourage DP, negatively impacting supply chain performance (SCP).

This study explored underlying causes of defensive pessimism, a self-limiting behavior among supply chain professionals. In understanding the role of DP, it is possible to enhance SCP by managing task complexity, external locus of control and job autonomy—predictors of defensive pessimism in work commitments.

The purpose of this paper is examining how financial inclusion can be enhanced in rural and remote areas in emerging economies through the adoption of Financial technologies. The study examines the direct influence of technological characteristics, facilitating conditions, trust and perceived risk on adoption of FinTech. Furthermore, the study examines the mediating effects of facilitating conditions and moderating effects of education level in adoption of FinTech.

The study employed quantitative research design. Stratified and simple random sampling were employed to identify areas in which respondents will be collected. Drop and Pick method was further employed to collect 275 valid and reliable responses. Structural equation modeling was used to analyze the data and assess the reliability and validity of the measurement model. Structural model analysis was employed to examine the hypothesized relationship.

The results show that compatibility, complexity agent trust, perceived risk and facilitating have significant influence on adoption of FinTech. Furthermore, the findings show that facilitating conditions mediate the relationship between all technological characteristics and FinTech adoption except the relationship between compatibility and FinTech. The study also has found that education level moderates the relationship between observability and FinTech adoption as well as trialability and FinTech adoption.

This study employed cross-sectional research-based techniques in collecting data for analyzing the hypothesized relationship. However, the drawback of cross-sectional may impact the findings of this study over a long time. Therefore, future studies must consider conducting longitudinal studies which may collect data over some time for analysis of the FinTech adoption. Furthermore, the generalization of these findings should be considered carefully by other countries which are not economically similar to Tanzania and developed countries. This also provides room for future studies to examine the same area in countries with different economic development.

This study contributes to knowledge into two folds: First there is limited knowledge on adoption of FinTech in emerging economies; the study addresses the knowledge gap by providing empirical findings which will help scholar. Furthermore, less studies have examined the moderating effects of facilitating condition in adoption of technology. This study addresses the knowledge gap by examining the moderating influence of moderating influence of facilitating conditions. Also, this study provides empirical findings which will help policymakers to implement strategy that will speed-up financial inclusion in rural and isolated areas in emerging economies.

The direct selling model adopted in the beauty and cosmetics industry puts female consumer entrepreneurs at the heart of the business model. A neglected phenomenon in female entrepreneurship, this study aims to focus on female sales agents’ capabilities that are linked to sales performance and examine which capabilities might be shaped and enhanced through coaching and training in an emerging economy context.

Survey data were generated from a sample of 249 female sales agents who agreed to participate in a coaching and training programme run by a focal firm. Data were collected in two phases to investigate the capabilities linked to sales performance pre-intervention and the impact of coaching and training on the relationships between the capabilities and sales performance post-intervention. The time-lag data were analysed using partial least squares structural equation modelling.

For female sales agents, self-efficacy and sales experience have a significant positive effect on adaptive sales performance both before and after the coaching and training intervention. In contrast, intellectual capital and self-motivation had a non-significant relationship with sales performance before the intervention. However, after the intervention, the relationship between these variables became positive and significant.

The study demonstrates the effects of pre- and post-coaching and training on female consumer entrepreneurs’ capabilities and the links to sales performance. These findings add critical empirical knowledge on how female consumer entrepreneurship may be developed and the role of entrepreneurship for female empowerment in the Asian context. Collectively, the findings bring to the fore the female sphere in consumer entrepreneurship research in emerging economies.

This study aims to explore how brands use brand personification techniques in real-time marketing on social media, particularly Twitter, and examine how these techniques impact consumer engagement, moderated by brand-event congruence levels.

Data included 464 tweets posted by 95 brands around three large events in 2019. The types of brand personification techniques and the level of brand-event congruence applied by the tweets were content-analyzed, and regression analyses were conducted to examine their linkages to consumer engagement metrics.

Results confirmed the use of diverse personification techniques in brands’ real-time marketing tweets as in the previous literature. The study also revealed a new personification technique, tacit expression, not reported in previous literature. The study also showed that the overall effectiveness of multimedia-based (vs caption-based) personification techniques in increasing consumer engagement on social media was greater, but their relative effectiveness varied depending on whether or not the event was functionally congruent with the brand.

The findings offer valuable suggestions to brand managers regarding prioritizing brand personification techniques and aligning brands’ social media marketing with real-time events to maximize the effectiveness of real-time marketing in boosting consumer engagement.

This research offers insights into the dynamic effects of different brand personification techniques in the new context of real-time marketing, extending the scope of literature on brand personification and anthropomorphism. The revelation of a new type of brand personification not captured in the extant literature is also a significant contribution.