The impact of influencers' multi-SNS use on followers’ behavioral intentions: An integration of cue consistency theory and social identity theory

The considerable marketing potential brought by the rapid growth of social media has been extensively examined in the literature, particularly in terms of the impact of influencers' recommendations on their followers' decisions. However, little attention has been given to how the individual influencers' use of multiple social networking sites affects their followers' behavioral intentions. Hence, this academic gap warrants further exploration. Drawing on cue consistency theory, social identity theory, and stimulus-organism-response framework, this research proposes three research questions and constructs an integrated research model to explore how the influencers' cue consistency affects the social identification of their followers, subsequently influencing their behavioral intentions. A structural equation modeling technique is performed to analyze the data of 510 valid respondents. The findings show that influencers' consistent cues (i.e., information and image consistency) across social media have positive impacts on followers' cognitive and affective identification toward the influencers. Furthermore, the determinants for followers' purchase intention and electronic word-of-mouth intention are affirmed to serve as both cognitive and affective identification. Especially, the results indicate that the relationships between followers’ social identifications and behavioral intentions are moderated by the type of influencer (i.e., lifestyle vs. review). Accordingly, the results indicate how the use of multiple social networking sites by influencers impacts the behavioral intentions of their followers. The findings offer new insights into influencer marketing and provide important lessons for marketers.     

Semiparametric time series regression modeling with a diverging number of parameters

Variable selection and error structure determination of a partially linear model with time series errors are important issues. In this paper, we investigate the regression coefficient and autoregressive order shrinkage and selection via the smoothly clipped absolute deviation penalty for a partially linear model with a divergent number of covariates and finite order autoregressive time series errors. Both consistency and asymptotic normality of the proposed penalized estimators are derived. The oracle property of the resultant estimators is proved. Simulation studies are carried out to assess the finite‐sample performance of the proposed procedure. A real data analysis is made to illustrate the usefulness of the proposed procedure as well.     

Social servicescape’s impact on customer perceptions of the hospitality brand – The role of branded social cues

This research examines how the social servicescape (i.e., employee-customer, employee-employee and customer-customer) impacts brand-related outcomes via branded social cues. Informed by theories related to cue consistency and conceptual fluency, results from three experimental studies conducted across sectors and scales of hospitality businesses (i.e., luxury hotel, high-end restaurant and limited-service hotel), indicate that branded social servicescape cues have direct, indirect and interactive effects on brand-related outcomes. In luxury contexts, when the brand’s personality is absent in employee-customer social cues, the negative effects were buffered if brand personality is reflected in employee-employee social cues. Conceptual fluency mediated the relationship between branded employee-customer social cues and brand-related outcomes, which was moderated by branded employee-employee social cues. Conceptual fluency also mediated the relationship between branded customer-customer social cues and brand-related outcomes. This research sheds light on how hospitality firms can leverage branded social cues to enhance customer evaluation of the hospitality brand.     

A field experiment to estimate the effects of anchoring and framing on residents’ willingness to purchase water runoff management technologies

Watersheds throughout the world have been severely polluted by nutrient-laden runoff that comes from industrial, agricultural, and residential sources. Efforts to reduce this runoff have focused on industrial and agricultural sources, while little attention has been paid to encouraging residents to reduce runoff from their properties. To study residents’ willingness to adopt landscaping practices that reduce runoff, we conducted a field experiment in the Delaware River watershed. In the experiment, over three hundred adults participated in a series of random-price auctions that revealed their willingness to pay (WTP) for five products that reduce nutrient runoff. To study how WTP can be influenced by attributes of the choice architecture, we randomized the starting bid values (anchors) and the way in which the external benefits of the five practices were framed. Compared to a neutral framing, a positive framing (using the product can improve water quality) increased average WTP by about one-third, while the estimated effect of a negative framing (failing to use the product can worsen water quality) was also positive, but smaller and not statistically different from zero. The estimated effect on average WTP from the anchor depends on how bids of $0 are modeled, but the results imply that higher anchors lead to higher WTP. Although we believe the magnitudes of our results should be considered suggestive and we recommend replications with higher statistical power, the results add to the evidence base that environmental programs can achieve policy-relevant gains in program performance through a series of small changes to the decision environment.     

Non-stationary additive utility and time consistency

Within a continuous time life cycle model of consumption and savings, I study the properties of the most general class of additive intertemporal utility functionals. They are not necessarily stationary, and do not necessarily multiplicatively separate a discount factor from “per-period utility”. I prove rigorously that time consistency holds if and only if the per-period felicity function is multiplicatively separable in $t$, the date of decision and in $s$, the date of consumption, or equivalently, if the Fisherian instantaneous subjective discount rate does not depend on $t$. The model allows to explain “anomalies in intertemporal choice” even when the agents are time consistent and various empirical regularities. On the other hand, the model allows to characterize mathematically the “effective consumption profile” of naive, time-inconsistent agents.     

When less is more? The contingent effect of product supply limitation in the release of new electronic products

In the market of consumer electronics, firms often limit their product supply to create a scarcity effect to entice consumers to buy their product. However, the outcome of such a strategy is not always desirable. In this study, we propose the product configuration level as a contingent variable that works with the supply level to affect the outcome of a supply limitation strategy. With a vignette-based experiment, we find that for a product with a superior configuration, consumers' purchase intention is boosted only if the supply is very limited. For a product with an inferior configuration, however, the supply limitation strategy does not work at any supply level. Therefore, the supply limitation strategy works only for a superior product configuration and at a fine-tuned supply level.     

Iterated VaR or CTE measures: A false good idea?

The purpose of this paper is twofold. Firstly, we consider different risk measures in order to determine the solvency capital requirement of a pension fund. Secondly, we illustrate the impact of the time horizon of long-term guarantee products on these capital. We consider a financial market modelled by a common Black–Scholes–Merton model. We neglect the mortality and underwriting risks by assuming that the pension fund is fully hedged against these risks, which allows us to keep understandable and tractable formulæ (the longevity risk will be a part of future researches). A portfolio is built in this market according to different strategies and the pension fund offers a fixed guaranteed rate on a certain time horizon. We begin with well-known static risk measures (value at risk and conditional tail expectation measures) and then we consider their natural dynamic generalization. In order to be time consistent, we consider their iterated versions by a backward iterations scheme. Within the dynamic setting, we show that solvency capital can be expensive and that attention must be paid to the safety level considered.     

环境质量变化对游客福利的影响——基于旅行费用和条件行为联合数据

环境质量是影响游客旅游需求及福利的重要因素,但单一使用陈述性偏好法或揭示性偏好法仍存在诸多局限性。为探究环境质量改变对游客需求及福利变化的具体影响,结合旅行费用与条件行为数据,在明确现有环境质量状况下景区价值基础上,评估环境质量改善与恶化两种情景下,游客消费者剩余的变化。结果表明,环境质量改变直接影响旅行次数,从而增加或减少消费者剩余,但不会通过影响游客旅行费用间接改变消费者剩余,实际行为与条件行为数据偏好存在一致性;白洋淀景区当前消费者剩余为909.09元/次;环境质量改善使游客平均旅行次数增加1.45次/年,并使每位游客每年的消费者剩余增加1 318.18元;环境质量恶化使游客平均旅行次数降低1.41次/年,并使每位游客每年的消费者剩余减少1 281.81元。     

TIME‐CONSISTENT AND MARKET‐CONSISTENT EVALUATIONS

We consider evaluation methods for payoffs with an inherent financial risk as encountered for instance for portfolios held by pension funds and insurance companies. Pricing such payoffs in a way consistent to market prices typically involves combining actuarial techniques with methods from mathematical finance. We propose to extend standard actuarial principles by a new market‐consistent evaluation procedure which we call “two‐step market evaluation.” This procedure preserves the structure of standard evaluation techniques and has many other appealing properties. We give a complete axiomatic characterization for two‐step market evaluations. We show further that in a dynamic setting with continuous stock prices every evaluation which is time‐consistent and market‐consistent is a two‐step market evaluation. We also give characterization results and examples in terms of g‐expectations in a Brownian‐Poisson setting.     

ON THE CONSISTENCY OF REGRESSION‐BASED MONTE CARLO METHODS FOR PRICING BERMUDAN OPTIONS IN CASE OF ESTIMATED FINANCIAL MODELS

In many applications of regression‐based Monte Carlo methods for pricing, American options in discrete time parameters of the underlying financial model have to be estimated from observed data. In this paper suitably defined nonparametric regression‐based Monte Carlo methods are applied to paths of financial models where the parameters converge toward true values of the parameters. For various Black–Scholes, GARCH, and Levy models it is shown that in this case the price estimated from the approximate model converges to the true price.