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Although user behaviors in social network service (SNS) have been well studied in prior literature, most of these studies focus on those behaviors with relatively deep user engagement such as information disclosure, while the underlying mechanisms that explain users’ shallow engagement behaviors (e.g. Like behavior) have been rarely discussed. To fill this research gap, the purpose of this paper is to propose and empirically test a research model to identify the antecedents of Like behavior.

This study identifies the distinctions between post behavior and Like behavior and develops a research model of Like behavior by emphasizing the role of sense of presence from the perspective of symbolic interactionism. The model is tested through a survey with 479 users of WeChat (a popular SNS tool in China). Structural equation modeling, SmartPLS in particular, is used for data analysis.

Three value perceptions, namely cognitive value, hedonic value and social value, are found to be positively associated with Like intention, and sense of presence is found to affect Like intention both directly and indirectly via the three value perceptions.

The research model is tested based on a specific SNS in China, so whether the conclusions can be applied to other research contexts should be further examined in future research. This study identifies the distinctions between post behavior and Like behavior and suggests to view the Like behavior from the perspective of symbolic interactionism.

The paper outlines ways to effectively promote SNS users’ Like behaviors by enhancing the functions related to three value perceptions, especially by enriching the ways that facilitate interpersonal interactions.

This paper is one of the first to distinguish Like behavior from post behavior in SNS, propose and empirically test a research model of Like behavior. In particular, this paper strengthens the important role of sense of presence from the perspective of symbolic interactionism which has rarely been investigated in prior studies.

This paper aims to providea comprehensive review of the concepts and definitions of green finance, and the importance of “green” impact investments today. The core challenge in combating climate change is reducing and controlling greenhouse gas emissions; therefore, this study explores the solutions green finance provides emphasizing their impact on the environment and firms' financial performance. With increasing attention to the concept of green finance, multiple forms of green financial tools have come to fruition; the most prominent are green bonds.

This paper compiles a comprehensive green bond dataset, presenting a statistical study of the evolution of the green bonds market from its first appearance in 2006 until 2021.

The green bond market has seen massive growth over the years reaching $1651.92bn as of 2021. Findings show that green bonds are working towards shifting from high carbon-emitting energy to renewable energy, which is vital to economic development and growth. In congruence, green bonds are aligned with the United Nation's sustainable development goals (SDGs) amounting to $550bn for 2020, with the five most covered SDGs amounting to over 60%.

With growing worldwide concern for global warming, green finance became the fuel that pushes the world to act in combating and mitigating climate change. Coupled with adopting the Paris Agreement and the SDGs, Green finance became a vital tool in creating a pathway to sustainable development, as it connects the financial world with environmental and societal benefits.

The purpose of this study is to investigate the determinants of customers’ intentions to use location-based services (LBS) offered by a hotel. The study examined whether hotel customers’ coupon proneness, trust, privacy concerns and familiarity with LBS are significant determinants of their intentions to use LBS.

An online survey using a scenario-based narrative was administered to collect data from participants who have smartphones and have stayed at a full-service hotel within the previous 12 months. A research model tested data collected from 402 hotel customers, using confirmatory factor analysis and structural equation modeling.

Three proposed determinants (i.e. familiarity, coupon proneness and trust) positively influenced customers’ intentions to use LBS. Out of the four dimensions of privacy concerns (concerns of collection, error, unauthorized secondary use and improper access), only concerns about data collection negatively influenced customers’ intentions to use a hotel’s LBS.

This study extends the literature on LBS adoption and other technology with privacy issues by modifying existing models and empirically testing it in the new context of hotels.

The purpose of this paper is to explore the relationship between general self-efficacy (GSE), job search self-efficacy (JSSE), extraversion and job search success within a sample of new entrants in the labour market. It is hypothesised that JSSE acts as a mediator between GSE and job search success. Evaluation of the hireability – made by expert interviewers – of new entrants involved in a job interview simulation is proposed as a job search success criterion. Moreover, the moderating role of extraversion on the relationship between JSSE and job search success is explored.

Data were collected on 177 graduates from an Italian university. Participants were involved in a simulation of an interview conducted by experts of the personnel selection process, who gave an evaluation. Macro PROCESS for SPSS was used to test the hypotheses.

GSE has an indirect effect on job search success via JSSE. Moreover, extraversion has a moderating effect on the JSSE–job search success relationship for more extraverted job seekers.

Job search and counselling practitioners should consider extraversion and personal differences to improve the effectiveness of interventions aimed at fostering new entrants' self-regulatory resources and behaviours during the job search.

This study contributes to the existing research about the job search process by testing a new and important job search success criterion, showing that GSE could help new graduates in establishing a specific self-efficacy, such as JSSE, and demonstrating that extraversion interacts with JSSE.

This study aims to examine the antecedents of tourist citizenship behavior (TCB). It also investigates the role of digital halal literacy (DHL) and religiosity in enhancing TCB.

This quantitative research used survey with questionnaire as the data collection methods. The samples of this study were 400 tourists who visited tourist destinations in five cities/municipals in West Sumatra Indonesia. This research used partial least square structural equation model as the data analysis tools.

This study found that satisfaction, trust and DHL are significant antecedents of TCB. In addition, satisfaction had a direct impact on TCB and influenced TCB through trust as a mediator. This study also found that religiosity had a direct influence on DHL, satisfaction and trust.

The findings will provide insights to tourist destination managers as well as the government on how to motivate tourists to participate in the development of Halal tourism in Indonesia. The tourists should gain sufficient knowledge or literacy about Halal, and especially in the digital context. Therefore, this will lead to their satisfaction, trust and willingness to participate in tourism development such as providing assistance to other tourists in the destinations.

This research has identified a new variable, DHL, which has not been addressed previously. This research has extended social exchange theory by establishing a relationship between TCB and DHL that has also not been previously explored. In addition, this study has investigated several relationships between DHL, satisfaction, trust and TCB and has shed new insights in the context of Halal tourism. This study has also provided a more comprehensive model of the relationship between DHL, satisfaction, trust and citizenship behavior specifically in Halal tourism research.

This study aims to investigate the effects of CEO gender on social enterprise (SE) value creation and the moderating effect of selective attention on SEs’ dual goals (i.e. relative attention to social versus economic goals).

The authors surveyed 596 active Taiwanese SEs to rate independent and moderating variables and received 191 responses (109 female and 82 male CEOs). The authors used external SE experts to evaluate each SE’s economic and social value creation, lowering the threat of common method bias and enhancing data quality.

Social value creation is higher with female chief executive officer (CEOs) (than with male CEOs), whereas economic value creation tends to be lower. But, attentional selection (i.e. changes in attention) to economic goals by female CEOs mitigates the negative relationship between female CEOs and economic value creation.

Gender diversity in the top management team is critical for dual-goal attainment. Decision-makers’ attention focus could vary along with the situation to achieve the desired outcomes. Thus, creating an attention structure under a given situation may help guide the decision-making process toward the desired performance for SEs.

Little research brings the attention-based view to investigate the effects of managerial gender roles on the dual-goal performance (i.e. social versus economic value creation) of SEs and test its contingency, and to the best of the authors’ knowledge, this study is the first to do so. This study also adopted a unique research design asking outside SE experts to provide the performance data.

The aggressive competition in the real estate market forces real estate developers to tackle the challenge of selecting the best project construction phasing alternative. The real estate industry is characterized by high costs, high profit and high risks. The schedules of real estate projects are also characterized by having large number of repetitive activities that are executed over a long duration. The repetitiveness, long duration of execution, the high amounts of money involved and the high risk made it desirable to leverage the impact of changes in phasing plans on net present value of amounts incurred and received over the long execution and selling duration. This also changes the project progress, and delivery time as well as their respective impact on customer degree of satisfaction. This research addresses the problem of selecting the best phasing alternative for real estate development projects while maximizing customer satisfaction and project profit.

The research proposes a model that generates all construction phasing alternatives and performs decision-making to rank all possible phasing alternatives. The proposed model consists of five modules: (1) Phasing Sequencing module, (2) Customer Satisfaction module, (3) Cash-In calculation module, (4) Cost Estimation module and (5) Decision-making module. A case study was presented to demonstrate the practicality of the model.

The proposed model satisfies the real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model generates all construction phasing alternatives and performs multi-criteria decision making to rank all possible phasing alternatives. It quantifies the score of the two previously mentioned criteria and ranks all solutions according to their overall score.

The research proposes a model that assist real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model can be used to conclude general guidelines and common successful practices to be used by real estate developers when deciding the construction phasing plan. In this study the model is based on business models where all the project units are sold, rental cases are not considered. Also, the budget limitations that might exist when phasing is not considered in the model computations.

The model can be used as a complete platform that can hold all real estate project data, process revenues and cost information for estimating profit, plotting cash flow profiles, quantifying the degree of customer satisfaction attributable to each phasing alternative and providing recommendation showing the best one. The model can be used to conclude general guidelines and common successful practices to be used by real estate developers when tackling the challenge of selecting construction phasing plans.

The financial sector’s growing interest in leveraging artificial intelligence (AI) for forecasting has been noted in recent years. In this chapter, we delve into the application of AI in financial forecasting within Indonesia’s stock market. Our primary focus is to assess how AI’s prediction potential can impact investors and financial regulators in this context. Our review spans existing literature on AI and financial forecasting, recent developments in the Indonesian stock market, and ethical and regulatory concerns that surround AI in finance. Our analysis indicates that AI can enhance forecast accuracy in Indonesia’s stock exchange; however, we must also consider limitations and challenges.

This study aims to examine the relationship between perceived risk and tourists’ trust. It also investigates the role of perceived value as a mediating variable on the link between perceived risk and trust. Moreover, the moderating role of religiosity on the link between perceived value and trust has also been highlighted.

The research population is all tourists who have visited West Sumatra Indonesia in the past two years. This research used a survey method using questionnaires and used purposive sampling as the sampling method. It collected 400 responses and after some preliminary tests, 352 usable responses have been analyzed. The authors used a covariance-based structural equation model using AMOS 24 as the data analysis tool.

This quantitative research found that perceived risk dimensions (health, environmental and financial risk) have significant impacts on perceived value. Perceived risk dimensions also have significant effects on trust except for health risk. It also found that perceived value has a significant impact on trust and finally, religiosity which has a significant moderating impact on the relationship between perceived value and trust.

This study is only one country study; hence, it has limited finding generalization. It needs to be expanded to other countries such as Southeast Asia countries. It only used three antecedents of trust, therefore, for future research; it might be extended to other antecedents such as cultural value, tourist efficacy and also some consequences of trust such as revisit intention and customer involvement. Finally, this is a cross-sectional study; hence, for future research, it might be expanded to a longitudinal study where the results are more generalized.

Trust will lead to tourist loyalty. Therefore, to establish trust, the managers need to provide the best services with pay attention to the tourist perceived risk. Moreover, it found that perceived risks will lead to tourists’ perceived value. Accordingly, to increase the tourist perceived value, the tourist destination managers have to minimize risk or uncertainty in the tourist destination such as environmental and health risk in the tourist destination. Finally, religiosity will strengthen the tourist trust, hence; the managers can attract and serve high religiosity tourists with Halal standard products and services.

This study has examined the relationship between perceived risk dimensions and perceived value which is not investigated in the previous studies. It also examined the mediating roles of perceived value on the link between perceived risk dimensions and trust. These mediating roles have not been addressed yet previously. Finally, it has also revealed a significant moderating effect of religiosity on the link between perceived value and trust which is neglected previously.

This paper aims to examine the interrelationships between user-centric measures and their impact on the firm’s perceived financial performance as the respondents’ decision-making role changes.

The data was collected jointly with SurveyMonkey, a marketing research company, from marketing professionals working in companies with at least limited experience deploying big data marketing analytics (BDMA) applications. The respondents originated from Canada and the USA, and out of 970 responses in the initial sample, 236 were working in companies with at least limited experience in BDMA deployment. The data analysis used partial least squares structural equation modeling and necessary condition analysis.

All hypotheses except one were accepted. Perceived value for money positively and significantly impacted user satisfaction, positively and significantly impacted perceived financial performance. Also, the decision-making role positively and significantly impacted the perceived value for money and user satisfaction but not the perceived financial performance.

The research contributes to understanding how the decision-maker’s role impacts the perceived user-related performance measures in the BDMA context.