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With the advancements of Internet of Things (IoT) and artificial intelligence (AI) in recent years, smart objects (SOs) have been widely applied in the lives of consumers to fulfill a variety of functions. This research aims to explore the new interaction experience between consumers and a smart speaker that can create the effect of customer engagement by enhancing the gendered voice and product smartness.

This study conducted a 2 × 2 × 2 between-subject experiment to validate the research model and the hypotheses.

The results indicate that a high level of interaction experience between the users and smart speaker devices increases customer engagement. Smart speaker devices that present female voices have a high product smartness, whereas high levels of interaction experience are more effective in customer engagement. Furthermore, the results also show a moderate effect of gendered voice and product smartness between the interaction experience levels and customer engagement.

This study contributes to the assemblage theory and the interaction experience levels between users and smart speaker devices in IoT. Based on the results, suggestions on enhancing the smartness ability and application services of new smart speaker devices are proposed. The findings of this study can promote a more continuous interaction between users and smart speakers.

Interest in psychological resilience has grown rapidly in the last couple of decades (Britt, Sinclair, & McFadden, 2016; King & Rothstein, 2010; Youssef & Luthans, 2007). Psychological resilience occurs when a person can “recover, re-bound, bounce-back, adjust or even thrive” in the face of adversity (Garcia-Dia, DiNapoli, Garcia-Ona, Jakubowski, & O’flaherty, 2013, p. 264). As such, resilience can be conceptualized as a state-like and malleable construct that can be enhanced in response to stressful events (Kossek & Perrigino, 2016). It incorporates a dynamic process by which individuals use protective factors (internal and external) to positively adapt to stress over time (Luthar, Cicchetti, & Becker, 2000; Rutter, 1987). Building on the dual-pathway model of resilience, we integrate adaptive and proactive coping to the resilience development process and add a heretofore unexamined perspective to the ways in which resilience changes over time. We propose that resilience development trajectories differ depending on the type of adversity or stress experienced in combination with the use of adaptive and proactive coping. We outline the need for future longitudinal studies to examine these relationships and the implications for developing resilience interventions in the workplace.

Low capital market literacy in Indonesian society is the cause of the low investment value in the capital market. It led to the establishment of the Indonesia Stock Exchange (IDX) investment gallery (IG). Its existence as a means of education and socialization is expected to increase capital market inclusion. This study analyzes the impact of the IG’s existence on investment interest in the capital market by taking a sample of West Java as the province with Indonesia’s largest population. The authors find that the public interest in visiting IG increases every year by an average of 38%, this is accompanied by an increase in opening new accounts in the capital market, with an average increase of 48% each year. The statistical tests results show that the greater the number of IGs, the greater the number of transactions in the capital market (p < 0.05). The results of this research can certainly be an input for the IDX to increase the number and activities of IG throughout Indonesia to increase Indonesia’s economy through capital market literacy and inclusion, besides that this research also produces a structured and systematic capital market education model. The research results can also reference countries with developing capital markets to adopt the IDX policies in attracting investors, especially domestic investors.

This paper aims to evaluate the stage and level of Henan province urbanization and provide basis for decision making.

At first, build the evaluation index system which includes 17 indexes in four classes so that can reflect the level of urbanization development of the entire region comprehensively. Then build the gray clustering model based on set pair. On this basis, the paper evaluates the urbanization process in Henan province. In order to get a clear understanding of the urbanization level in Henan province, the paper selects several typical provinces and compares them with Henan province in urbanization process.

The results show that the urbanization level in Henan province belongs to the general level; there is a gap in urbanization process between Henan province and other advanced provinces.

The paper put forward a method to evaluate the urbanization process in Henan province and get a clear understanding of the urbanization level in Henan province.

The paper combines the set pair analysis and the gray fixed weight cluster method based on triangular whiten weight function, which can avoid the defect that the assessment result is too vague and the difference is not significant.

The purpose of this paper is to construct a prediction model of three-parameter interval grey number based on kernel and double information domains to expand the modeling object of grey prediction model from interval grey number to three-parameter interval grey number.

First, the study decomposes the grey valued interval into upper and lower cells with the “center of gravity” as the dividing point and defines the upper and lower information domains of the three-parameter interval grey number. Second, it calculates the kernel, the upper and lower information domains of the three-parameter interval grey number. Then, it constructs the prediction model for kernel sequence and upper and lower information domain sequences, respectively. By deducing the time response expressions of “center of gravity”, lower and upper limits of three-parameter interval grey number, a prediction model of three-parameter interval grey number based on kernel and double information domains is obtained.

This paper provides a prediction model of three-parameter interval grey number based on kernel and double information domains, and the example analysis shows that the method proposed in this paper has higher prediction accuracy and practicality.

In this paper, the modeling object of grey prediction model is extended to the three-parameter interval grey number, so it can be used for the prediction of uncertainty problems, such as stock changing trend, temperature and so on.

By decomposing the grey valued interval into upper and lower cells with the “center of gravity” as the dividing point, gives the definition of upper and lower information domains and then obtains a new method for whitening the three-parameter interval grey number.

In this essay, a new NDAGM(1,N,α) power model is recommended to resolve the hassle of the distinction between old and new information, and the complicated nonlinear traits between sequences in real behavior systems.

Firstly, the correlation aspect sequence is screened via a grey integrated correlation degree, and the damped cumulative generating operator and power index are introduced to define the new model. Then the non-structural parameters are optimized through the genetic algorithm. Finally, the pattern is utilized for the prediction of China’s natural gas consumption, and in contrast with other models.

By altering the unknown parameters of the model, theoretical deduction has been carried out on the newly constructed model. It has been discovered that the new model can be interchanged with the traditional grey model, indicating that the model proposed in this article possesses strong compatibility. In the case study, the NDAGM(1,N,α) power model demonstrates superior integrated performance compared to the benchmark models, which indirectly reflects the model’s heightened sensitivity to disparities between new and old information, as well as its ability to handle complex linear issues.

This paper provides a scientifically valid forecast model for predicting natural gas consumption. The forecast results can offer a theoretical foundation for the formulation of national strategies and related policies regarding natural gas import and export.

The primary contribution of this article is the proposition of a grey multivariate prediction model, which accommodates both new and historical information and is applicable to complex nonlinear scenarios. In addition, the predictive performance of the model has been enhanced by employing a genetic algorithm to search for the optimal power exponent.

Customer experience is a relevant concept in marketing and tourism research since its correct understanding allows companies to achieve competitive advantage and service providers can reach several outcomes such as customer engagement, loyalty, and customer satisfaction. This chapter aims to analyze one of the main outcomes of the customer experience, the customer satisfaction through online reviews, and using spatial analysis as a tool to incorporate the contextual nature of the customer experience. Thus, our study considers online rating as a measure of customer satisfaction and tries to analyze the impact of actions under the control of the service provider (price and objective quality) and actions under the control of the customer (subjective quality) on customer satisfaction.

With the Spanish hotel industry as a study framework, an empirical study is developed to analyze, through geographically weighted regression techniques, the relationship between price, objective quality and subjective quality, and online ratings given by consumers with a sample of 1870 of geolocated hotels in Spain. The findings show how a premium price, depending on the geolocation, is an indicator for better customer experiences, and they also show that objective quality is the antecedent of customer experience whose positive effect on customer satisfaction is geographically more widespread. Results show contradictory effects of subjective quality, while in some areas subjective quality does not match the product fit of customers, in others it allows hotels to provide more satisfactory experiences.

The purpose of this paper is to propose a dynamic multi-attribute decision-making method based on the prospect theory for dealing with the dynamic multi-attribute decision-making problem with three-parameter interval grey number.

First, the kernel and comparison rule of three-parameter interval grey numbers are defined, which are the basis of collecting and sorting grey numbers. Next, the prospect value function is determined in view of the decision-making information with different time points as the reference points. Then, an optimal model for solving the attribute weight and time weight is constructed based on the grey entropy principle.

The paper provides a dynamic grey interrelation decision method based on the prospect theory with three-parameter interval grey number, and the example analysis shows that the method proposed in this paper has validity and rationality.

If we have a better understanding of the weights of different reference points, it is possible to receive a more reasonable expression for the comprehensive prospect utility value function.

The paper provides a grey interrelation decision method based on the prospect theory, which can help the decision maker deal with the dynamic multi-attribute decision-making problems under the uncertain environment.

The paper proposes the kernel and ranking method of three-parameter interval grey number, and uses different time points as the reference points to define the prospect value function. Furthermore, this paper structures a dynamic grey interrelation decision method with three-parameter interval grey number based on the prospect theory.

This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experiment and investigates the impact of capital market liberalization on the corporate debt maturity structure. It also aims to provide some policy implications for corporate debt financing and further liberalization of the capital market in China.

Employing the exogenous event of Shanghai-Shenzhen-Hong Kong Stock Connect and using the data of Chinese A-share firms from 2010 to 2020, this study constructs a difference-in-differences model to examine the relationship between capital market liberalization and corporate debt maturity structure. To validate the results, this study performed several robustness tests, including the parallel test, the placebo test, the Heckman two-stage regression and the propensity score matching.

This paper finds that capital market liberalization has significantly increased the proportion of long-term debt of target firms. Further analyses suggest that the impact of capital market liberalization on the debt maturity structure is more pronounced for firms with lower management ownership and non-Big 4 audit. Channel tests show that capital market liberalization improves firms’ information environment and curbs self-interested management behavior.

This research provides empirical evidence for the consequences of capital market liberalization and enriches the literature on the determinants of corporate debt maturity structure. Further this study makes a reference for regulators and financial institutions to improve corporate financing through the governance role of capital market liberalization.

The aim of this paper is to provide additional insights on the association between real earnings management (REM) and crash risk, particularly from the perspective of an emerging market economy. It also examines the moderation role that internal and external corporate governance may play in this area.

Relying on archival data from the RESSET and CSMAR databases over a timeframe from 2010 to 2018 of China listed company, the authors test the hypotheses by regressing common measures of crash risk on the treatment variable (REM) and crash risk control variables identified in the prior crash risk literature. The authors also introduce monitoring proxies (internal controls as an internal governance and institutional ownership as an external governance) and assess how effective internal and external governance moderate the relation between REM and stock price crash risk.

The results suggest firms with higher REM have a significantly greater stock price crash risk, and that this association is mitigated by external monitoring. That is, greater institutional ownership, particularly pressure insensitive owners, mitigates the impact of REM on stock price crash risk. However, internal control does not mitigate the association between REM and stock price crash risk.

Following the passage of the Sarbanes–Oxley (SOX) Act, prior research has documented an increase in the use of REM and a positive association between REM and cash risk. The authors demonstrate that they persist in one of the largest emerging markets where institutional regulations, market conditions and corporate behaviors are different from those in developed markets. Also, the assessment of the moderation effect of internal and external governance mechanisms could have meaningful implications for investors and regulators in Chinese and other emerging markets.